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. 2022 Nov 20;7(4):204. doi: 10.3390/biomimetics7040204

Serval Optimization Algorithm: A New Bio-Inspired Approach for Solving Optimization Problems

Mohammad Dehghani 1, Pavel Trojovský 1,*
Editor: Stuart Burgess1
PMCID: PMC9703967  PMID: 36412732

Abstract

This article introduces a new metaheuristic algorithm called the Serval Optimization Algorithm (SOA), which imitates the natural behavior of serval in nature. The fundamental inspiration of SOA is the serval’s hunting strategy, which attacks the selected prey and then hunts the prey in a chasing process. The steps of SOA implementation in two phases of exploration and exploitation are mathematically modeled. The capability of SOA in solving optimization problems is challenged in the optimization of thirty-nine standard benchmark functions from the CEC 2017 test suite and CEC 2019 test suite. The proposed SOA approach is compared with the performance of twelve well-known metaheuristic algorithms to evaluate further. The optimization results show that the proposed SOA approach, due to the appropriate balancing exploration and exploitation, is provided better solutions for most of the mentioned benchmark functions and has superior performance compared to competing algorithms. SOA implementation on the CEC 2011 test suite and four engineering design challenges shows the high efficiency of the proposed approach in handling real-world optimization applications.

Keywords: bio-inspired, engineering systems, optimization, metaheuristic, serval, exploration, exploitation

1. Introduction

An optimization problem is a type of problem that has several feasible solutions. Optimization is the process of searching for the best solution among possible solutions for a problem [1]. Optimization is used in various science, engineering, technology, and real-world applications [2]. Finding the best optimum can achieve multiple benefits, such as reducing costs, maximizing profits, improving equipment efficiency, etc. For this reason, finding suitable and effective solutions for optimization applications is a fundamental challenge for scientists. From a mathematical point of view, an optimization problem is characterized by three main parts: decision variables, objectives, and constraints [3].

Problem-solving techniques in dealing with optimization tasks are classified into two groups: deterministic and stochastic approaches [4]. Deterministic methods in two categories, gradient-based and non-gradient-based, are effective in handling optimization problems that are linear, convex, differentiable, and have a continuous search space [5]. Among the deterministic methods of solving optimization problems are approaches such as dynamic programming, Newton methods, linear programming, gradient method, quadratic programming, and simplex methods, among the deterministic methods of solving optimization problems [6]. However, as optimization problems become more complex, the number of decision variables increases, and for many real-world applications, deterministic approaches lose their effectiveness. Features such as complexity, non-linearity, non-convexity, non-differentiability, discretization, and problems with high-dimensions objective functions or a discrete search space, etc., are the nature of many modern optimization problems and real-world applications. Such characteristics lead to disruption of the efficiency of deterministic approaches and the problem that they are getting stuck in local optima [7]. Such difficulties in deterministic approaches have led researchers to develop new methods called stochastic approaches to deal with optimization problems. Advantages such as simplicity of concepts, easy implementation, no dependence on the type of problem, no need for derivative information, efficiency in non-linear, non-convex, NP-hard, complex and high-dimensional problems, efficiency in non-linear, and unknown search spaces have made metaheuristic algorithms popular and widespread [8].

The process of solution finding in metaheuristic algorithms starts with the random generation of a number of feasible solutions in the search space. Then, these solutions are improved during iterations of the algorithm based on different steps of updating the metaheuristic algorithms. Finally, after the full implementation of the algorithm, the best feasible solution found during the iterations is presented as a solution to the problem [9]. Metaheuristic algorithms perform the search process in the problem-solving space at both global and local levels. Global search with the concept of exploration ability leads to scanning different regions of the problem-solving space and avoiding getting stuck in local optima. Local search with the concept of exploitation ability leads to finding better solutions in promising areas of search space. In addition to the appropriate quality in exploration and exploitation, the primary key to the success of metaheuristic algorithms in solving optimization problems is to create a balance between exploration and exploitation during algorithm iterations [10].

The nature of random search in metaheuristic algorithms leads to the fact that there is no guarantee that the solutions obtained from these methods are the best solution to the problem. However, these solutions are acceptable as quasi-optimal solutions. A metaheuristic algorithm that can provide better pseudo-optimal solutions closer to the global optimum has a superiority in competition with other metaheuristic algorithms. The desire of scientists to achieve better and more effective solutions for optimization applications has led to the introduction of numerous metaheuristic algorithms [11].

Due to the fact that numerous metaheuristic algorithms have been developed so far, the main research question is: Does the world still need to introduce newer metaheuristic algorithms? No Free Lunch (NFL) [12] theorem answers the question that the effective performance of a metaheuristic algorithm in solving a set of optimization problems does not guarantee the same performance of that algorithm in all optimization applications. According to the NFL theorem, there is no assumption about the efficiency or non-efficiency of an algorithm in handling an optimization problem. Therefore, it can only be claimed that a particular algorithm is the best optimizer for some optimization tasks. Instead, the NFL theorem encourages and motivates researchers to be able to provide more effective solutions for optimization tasks by designing new metaheuristic algorithms. This theorem has also inspired the authors of this article to develop a new metaheuristic algorithm to deal with optimization problems.

According to the concept of the NFL theorem, the randomness of the search process in metaheuristic algorithms, the failure to guarantee the achievement of the global optimal by metaheuristic algorithms, and failure of a metaheuristic algorithm to provide similar performance in all optimization applications, the world always needs to introduce newer metaheuristic algorithms to provide more effective solutions for optimization problems. In this regard, the goal of the paper is to introduce a new metaheuristic algorithm to provide an effective problem-solving tool for researchers to be able to achieve better solutions for optimization tasks. The proposed new metaheuristic algorithm is developed based on simulating the natural behavior of serval during hunting and chasing process. In the proposed method, by simulating the search process in two phases of (i) exploration with the aim of increasing the global search power of the algorithm in order to identify the main optimal area and prevent getting stuck in the local optimal and the (ii) exploitation with the aim of increasing the local search power in order to achieve better solutions, it is expected acquired more effective solutions that are closer to the global optimum in solving optimization problems.

This paper’s novelty and innovative aspects in designing a new optimizer called the Serval Optimization Algorithm (SOA) to deal with optimization tasks in different sciences. The main contributions of this paper are listed as follows:

  • SOA is a nature-inspired approach that simulates natural serval behaviors.

  • The essential inspiration of SOA is the serval strategy when hunting in three stages: selection, attack, and chase.

  • The mathematical model of SOA is presented in two phases: exploration and exploitation.

  • SOA capability is benchmarked in optimizing the CEC 2017 and CEC 2019 test suites.

  • The performance of SOA in handling real-world applications is evaluated on the CEC 2011 test suite and four engineering design challenges.

  • The performance of the proposed SOA approach is challenged in comparison with twelve well-known metaheuristic algorithms.

The article is organized as follows: a literature review is presented in Section 2. The proposed SOA approach is introduced and modeled in Section 3. Simulation studies and results are presented in Section 4. The effectiveness of SOA in handling real-world applications is challenged in Section 5. Conclusions and suggestions for future research are provided in Section 6.

2. Literature Review

Metaheuristic algorithms have been developed based on the simulation of various natural phenomena, natural behaviors of animals, birds, aquatic animals, insects, and other living creatures in the wild, physical laws and phenomena, biological sciences, genetics, human behaviors and interactions, rules of games, and other evolutionary phenomena. Therefore, based on the main idea used in the design, metaheuristic algorithms are classified into five groups: swarm-based, evolutionary-based, physics-based, game-based, and human-based.

Swarm-based algorithms are developed by being inspired by the swarming behavior of living organisms, such as, e.g., animals, birds, insects, and aquatics in nature. The most famous algorithms of this group can be mentioned: Particle Swarm Optimization (PSO) [13], Artificial Bee Colony (ABC) [14], and Ant Colony Optimization (ACO) [15]. PSO is developed based on the simulation of the movement of flocks of birds or fish that are searching for food. ABC is introduced inspired by the activities of a honey bee colony in obtaining food resources. ACO is designed based on modeling the ability of ants to find the optimal route between the nest and the food source. Searching for food resources and hunting strategy for providing food are natural behaviors among animals that are employed in the design of numerous metaheuristic algorithms such as the Coati Optimization Algorithm (COA) [16], Reptile Search Algorithm (RSA) [17], White Shark Optimizer (WSO) [18], Honey Badger Algorithm (HBA) [19], Golden Jackal Optimization (GJO) [20], African Vultures Optimization Algorithm (AVOA) [21], Grey Wolf Optimizer (GWO) [22], Whale Optimization Algorithm (WOA) [23], Marine Predator Algorithm (MPA) [24], and Tunicate Swarm Algorithm (TSA) [25].

Evolutionary-based algorithms are introduced with inspiration from biological and genetics sciences, random operators, concepts of natural selection, and survival of the fittest. Genetic Algorithm (GA) [26] and Differential Evolution (DE) [27] are among the most well-known and widely used metaheuristic algorithms that are designed based on reproduction simulation, Darwin’s theory of evolution, and stochastic operators such as selection, crossover, and mutation.

Physics-based algorithms are designed with inspiration from phenomena, concepts, and laws in physics. The Simulated Annealing (SA) [28] algorithm is one of the most famous physics-based approaches. The modeling of the metal annealing phenomenon in metallurgy has been the main idea in its design. Physical forces are the origin of the creation of algorithms such as the Spring Search Algorithm (SSA) [29] based on spring tensile force, the Gravitational Search Algorithm (GSA) [30] based on gravitational attraction force, and the Momentum Search Algorithm (MSA) [31] based on momentum force. The phenomenon of physical changes in water has been the main idea in Water Cycle Algorithm (WCA) design [32]. Concepts of cosmology have been the origin of Black Hole Algorithm (BHA) design [33]. Some of the most popular physics-based methods are: Equilibrium Optimizer (EO) [34], Electro-Magnetism Optimization (EMO) [35], Multi-Verse Optimizer (MVO) [36], Archimedes Optimization Algorithm (AOA) [37], Thermal Exchange Optimization (TEO) [38], and Lichtenberg Algorithm (LA) [39].

Game-based algorithms are developed with inspiration from various individual and group games, the behavior of players, coaches, referees, and other people influencing the game. Football Game Based Optimization (FGBO) [40] and Volleyball Premier League (VPL) [41] are two game-based approaches that are designed based on the modeling of holding league competitions. The common aspect of many games is the effort of players to earn points, which is the origin of the design of algorithms, including Darts Game Optimizer (DGO) [42], Puzzle Optimization Algorithm (POA) [43], Hide Object Game Optimizer (HOGO) [44], Archery Algorithm (AA) [8], and Tug of War Optimization (TWO) [45].

Human-based algorithms are introduced by taking inspiration from human behaviors, interactions, and thoughts. One of this group’s most widely used algorithms is Teaching-Learning Based Optimization (TLBO) [46], which is introduced based on the modeling of human behaviors between students and teachers in the classroom. Teammates’ efforts to achieve team goals have been the design idea of the Teamwork Optimization Algorithm (TOA) [47]. The therapeutic activities of doctors in treating patients have inspired the design of Doctor and Patient Optimization (DPO) [48]. Some of the other popular human-based methods are: Ali Baba and the Forty Thieves (AFT) [49], Coronavirus Herd Immunity Optimizer (CHIO) [50], War Strategy Optimization (WSO) [51], and Gaining Sharing Knowledge based Algorithm (GSK) [52].

Based on the best knowledge obtained from the literature review, no metaheuristic algorithm has been designed so far based on the simulation of natural behaviors of servals. At the same time, the serval’s strategy during hunting and capturing prey is an intelligent process with the potential to design an optimizer. In order to address this research gap, in this paper, the natural behavior of servals during hunting in nature is employed in the design of a new bio-inspired metaheuristic algorithm, which is introduced and modeled in the next section.

3. Serval Optimization Algorithm

This section is dedicated to the introduction and mathematical modeling of the proposed Serval Optimization Algorithm (SOA) approach.

3.1. Inspiration of SOA

Serval is a skilled predator that hunts its prey in three stages. First, using its strong sense of hearing, it identifies the position of the prey and observes it for up to 15 min without moving. Then, in the second stage, it moves towards the prey, jumps up to a height of 4 meters in the air with all four feet, and attacks this prey with its front paws. Finally, in the third stage, in a chasing process by running and jumping to catch the fleeing prey, the serval kills it and starts eating it [53].

Serval’s strategy during hunting is one of the most characteristic natural behaviors of this animal. This strategy is an intelligent process that can inspire the design of a new metaheuristic algorithm. Modeling the three-stage serval strategy during hunting is employed in SOA design, which is discussed below.

3.2. Algorithm Initialization

The proposed SOA approach is a population-based optimizer that is able to provide suitable solutions for optimization problems by using the search power of its search agents. Servals that look for prey in nature have a similar approach to the mechanism of search agents in identifying the optimal solution. For this reason, from a mathematical point of view, servals form the SOA population that seeks to achieve the optimal solution in the search space. Therefore, each serval is a candidate solution for the problem whose position in the search space determines the values of the decision variables. From a mathematical point of view, each serval is a vector, and their population together forms the SOA population matrix, which can be represented according to Equation (1). The initial position of servals in the search space at the beginning of the implementation of the algorithm is randomly generated using Equation (2).

X=[X1XiXN]N×d=[x1,1x1,jx1,dxi,1xi,jxi,dxN,1xN,jxN,d]N×d, (1)
xi,j=lbj+ri,j·(ubjlbj), i=1,2, , N and j=1,2, ,d, (2)

where X denotes the population matrix of serval locations, Xi is the ith serval (candidate solution), xi,j is its jth dimension in search space (decision variable), N denotes the number of servals, d is the number of decision variables, ri,j are random numbers in the interval [0,1], lbj, and ubj are the lower and upper bounds of the jth decision variable, respectively.

Since each serval is a candidate solution for the problem, the objective function of the problem can be evaluated based on the proposed values of each serval for the decision variables. Then, according to Equation (3), a vector can represent the values of the problem’s objective function.

F=[F1FiFN]N×1=[F(X1)F(Xi)F(XN)]N×1, (3)

where F denotes the vector of objective function values and Fi denote to the obtained objective function value from the ith serval.

Among the calculated values for the objective function, the best value is identified as the best candidate solution, and the member corresponding to it is determined as the best member of the population. Considering that in each SOA iteration, the positions of all population members are updated, of course, the best member should be updated in each iteration.

3.3. Mathematical Modelling of SOA

The process of updating SOA population members in the search space has two phases based on simulating the serval hunting strategy in nature. These phases are intended to model exploration in global search and exploitation in local search in SOA design.

3.3.1. Phase 1: Prey Selection and Attacking (Exploration)

The serval is an efficient predator that uses its strong sense of hearing to identify the location of its prey and then attack it. In the first phase of SOA, the positions of servals are updated based on the simulation of these two strategies. This update causes big changes in the position of servals and leads to a detailed scanning of the search space. The purpose of this phase of SOA is to increase the power of SOA exploration in global search and to identify the main optimal region.

In the SOA design, the position of the population’s best member is considered the prey position. First, the new position for the serval is calculated using Equation (4) to model the serval’s attack on the prey. Then, if this new position improves the value of the objective function, it replaces the previous serval position according to Equation (5).

xi,jP1=xi,j+ri,j·(PjIi,j·xi,j), i=1,2, , N and j=1,2, ,d, (4)
Xi={XiP1, FiP1<FiXi, else (5)

where XiP1 denotes the new position of the ith serval based on the first phase of SOA, xi,jP1 is its jth dimension, FiP1 is its objective function value, ri,j are random numbers in interval [0,1], P denotes the prey location, Pj is its jth dimension, Ii,j are numbers randomly selected from the set {1,2}, N is the total number of servals population, and d is the number of decision variables.

3.3.2. Phase 2: Chase Process (Exploitation)

After attacking the prey, the serval tries to stop the prey by leaping in a chase process, then kills it and feeds on it. In the second phase of SOA, this serval strategy is employed in updating the population position of SOA. The simulation of the chase process causes small changes in the positions of the servals in the search space. In fact, the purpose of this SOA phase is to increase the exploitation power of SOA in local search and find better solutions. In order to mathematically model the chasing process between the serval and the prey, a new random position near the serval is calculated using Equation (6). This new position, provided that it improves the value of the objective function, replaces the previous position of the corresponding serval according to Equation (7).

xi,jP2=xi,j+ri,j·(ubjlbj)t, i=1,2, , N, j=1,2, ,d, and t=1,2, , T, (6)
Xi={XiP2, FiP2<Fi,Xi, else, (7)

where XiP2 represents the new position of the ith serval based on second phase of SOA, xi,jP2 is its jth dimension, FiP2 denotes its objective function value, t is the iteration counter of the algorithm, and T represents to the total number of algorithm iterations.

3.4. Repetition Process, Pseudocode, and Flowchart of SOA

By updating all servals based on the first and second phases of SOA, the first iteration of the algorithm is completed. Then, based on the new positions of the servals and the new values obtained for the objective function, the algorithm enters the next iteration. The operation of updating the positions of servals is repeated until the last iteration of the algorithm based on Equations (4)–(7). After the complete implementation of SOA, the best candidate solution obtained during the algorithm’s execution is introduced as the solution to the problem. The SOA implementation process is presented in the form of a flowchart in Figure 1, and its pseudo code is presented in Algorithm 1.

Figure 1.

Figure 1

Flowchart of the proposed SOA.

Algorithm 1 Pseudocode of the SOA.
Start SOA.
1. Input problem information: variables, the objective function, and constraints.
2. Set the population size (N) and the total number of iterations (T)
3. Generate the initial population matrix at random.
4. Evaluate the objective function.
5. For t = 1 to N
6.   For i = 1 to N
7.   Phase 1: Prey selection and attacking (exploration)
8.     Update the best member of population as prey location.
9.     Calculate the new position of the ith SOA member based on attack simulation using Equation (4). xi,jP1xi,j+ri,j·(PjIi,j·xi,j)
10.     Update the ith SOA member using Equation (5). Xi{XiP1, FiP1<Fi,Xi, else,
11.   Phase 2: Chase process (exploitation)
12.     Calculate new position of the ith SOA member based on simulation the chase using Equation (6).
xi,jP2xi,j+ri,j·(ubjlbj)t
13.     Update the ith SOA member using Equation (7). Xi{XiP2, FiP2<Fi,Xi, else,
14.   end
15.   Save the best candidate solution so far.
16. end.
17. Output the best quasi-optimal solution obtained with the SOA.
End SOA.

3.5. Computational Complexity of SOA

This subsection is dedicated to the computational complexity analysis of the proposed SOA approach. SOA initialization operation has a complexity equal to O(Nd), where N is the number of servals and d is the number of decision variables. The process of updating the SOA population and calculating the objective function in two phases has a complexity equal to O(2NdT), where T is the maximum number of algorithm iterations. Therefore, the total computational complexity of SOA is O(Nd(1+2T)).

4. Simulation Studies and Results

This section is dedicated to evaluating the performance of SOA in solving optimization problems and achieving solutions for these problems. For this purpose, thirty-nine standard benchmark functions from the CEC 2017 test suite and CEC 2019 test suite have been employed. The CEC 2017 test suite has 30 benchmark functions, including 3 unimodal functions C17-F1 to C17-F3, 7 multimodal functions C17-F4 to C17-F10, 10 hybrid functions C17-F11 to C17-F20, and 10 composition functions C17-F21 to C17-F30. The C17-F2 function is not considered in the simulations due to its unstable behavior. The complete information of the CEC 2017 test suite is described in [54]. CEC 2019 test suite has 10 hard benchmark functions, the complete information of which is described in [55]. The quality of the SOA approach in optimization has been compared with the performance of twelve well-known metaheuristic algorithms. These algorithms include: (i) widely used and famous methods: GA, PSO, (ii) high cited methods: GSA, TLBO, MVO, GWO, WOA (iii) recently published methods MPA, TSA, RSA, AVOA, and WSO. The adjusted values for the parameters of competitor algorithms are listed in Table 1.

Table 1.

Control parameters values.

Algorithm Parameter Value
GA
Type Real coded
Selection Roulette wheel (Proportionate)
Crossover Whole arithmetic (Probability=0.8,
α[0.5, 1.5])
Mutation Gaussian (Probability=0.05)
PSO
Topology Fully connected
Cognitive and social constant (C1,C2)=(2, 2)
Inertia weight Linear reduction from 0.9 to 0.1
Velocity limit 10% of dimension range
GSA
Alpha, G0, Rnorm, Rpower 20, 100, 2, 1
TLBO
TF: teaching factor TF= round  [(1+rand)]
random number rand is a random number between 0 and 1.
GWO
Convergence parameter (a) a: Linear reduction from 2 to 0.
MVO
wormhole existence probability (WEP) Min(WEP)=0.2 and Max(WEP)=1.
Exploitation accuracy over the iterations (p) p=6.
WOA
Convergence parameter (a) a: Linear reduction from 2 to 0.
r is a random vector in [0, 1].
l is a random number from [1, 1].
TSA
Pmin and Pmax  1, 4
c1,c2,c3 random numbers lie in the interval [0, 1].
MPA
Constant number P=0.5
Random vector R is a vector of uniform random numbers in [0, 1].
Fish Aggregating Devices (FADs) FADs=0.2
Binary vector U=0 or 1
RSA
Sensitive parameter β=0.01
Sensitive parameter α=0.1
Evolutionary Sense (ES) ES: randomly decreasing values between 2 and −2
AVOA
L,L2 0.8, 0.2
w 2.5
P1,P2,P3 0.6, 0.4, 0.6
WSO
Fmin and Fmax 0.07, 0.75
τ,a0,a1,a2 4.125, 6.25, 100, 0.0005

SOA and competitor algorithms are employed to optimize the 39 benchmark functions mentioned above. Simulation results are presented using six indicators: mean, best, worst, standard deviation (std), median, and rank.

4.1. Evaluation the CEC 2017 Test Suite

To analyze the quality of SOA and competitor algorithms in handling optimization problems, they have been implemented on the CEC 2017 test suite for dimensions d equal to 10, 30, 50, and 100. Table 2, Table 3, Table 4 and Table 5 present the results obtained from these implementations.

Table 2.

Optimization results of the CEC 2017 test suite (for the dimension d=10).

SOA WSO AVOA RSA MPA TSA WOA MVO GWO TLBO GSA PSO GA
C17-F1 mean 100.827 3072.047 4092.864 1.09 × 1010 100 6.28 × 109 8734,850 5565.472 43,130,985 92,363,844 789.6176 3796.408 16,141,320
best 100.5137 501.1341 116.6581 9.41 × 109 100 14,208,120 2734,095 1329.943 36,727.39 75,427,798 100.0205 352.658 3,264,472
worst 100.9824 7395.231 12,699.46 1.3 × 1010 100 1.15 × 1010 21,710,549 10,084.16 1.64 × 108 1.31 × 108 1902.646 5631.975 38,820,667
std 0.214676 3233.023 5877.613 1.61 × 109 5.28 × 10−6 4.84× 109 8,902,280 4689.867 80,613,752 26,120,139 779.9287 2493.307 15,706,283
median 100.9061 2195.912 1777.667 1.06 × 1010 100 6.82× 109 5,247,378 5423.893 4,281,710 81,580,648 577.9017 4600.499 11,240,071
rank 2 4 6 13 1 12 8 7 10 11 3 5 9
C17-F3 mean 300 464.5135 302.0192 10,267.95 300 12,685.25 3260.516 300.0635 2593.578 858.8106 10,918.38 315.5806 23,430.61
best 300 300.1927 300 5527.263 300 8573.571 669.5847 300.0286 329.8934 607.0993 6863.28 313.0498 15,808.63
worst 300 844.4021 304.319 13,744.58 300 16,868.14 7558.956 300.1108 4362.243 1095.099 14,847.31 319.4459 28,582.79
std 1.89 × 10−13 254.8057 2.342749 3757.315 4.04 × 10−11 3775.747 2994.478 0.038787 1853.797 199.5407 3293.007 2.79139 5569.145
median 300 356.7296 301.8789 10,899.98 300 12,649.64 2406.762 300.0573 2841.088 866.5219 10,981.47 314.9134 24,665.52
rank 1 6 4 10 2 12 9 3 8 7 11 5 13
C17-F4 mean 403.0484 407.2957 405.0707 1414.847 400 452.2675 452.3776 403.3356 417.5088 429.1642 404.8591 405.1688 413.6139
best 402.5089 406.6334 401.3246 874.8043 400 408.4697 407.1862 400.7995 407.7759 410.0639 403.8009 400.3294 408.6659
worst 403.9619 407.9785 406.9653 1943.823 400 484.0319 516.3257 405.041 446.4927 474.1362 406.4845 411.3318 417.5843
std 0.64045 0.610881 2.657606 456.3131 2.19 × 10−7 35.3625 51.19739 1.911616 19.32268 30.32581 1.230735 5.510745 4.388246
median 402.8615 407.2854 405.9964 1420.38 400 458.2842 442.9992 403.751 407.8834 416.2283 404.5755 404.5069 414.1026
rank 2 7 5 13 1 11 12 3 9 10 4 6 8
C17-F5 mean 520.0481 517.9215 547.3819 578.3821 524.1491 555.48 565.3388 522.6386 520.2654 532.6729 557.956 531.8387 531.6347
best 506.9647 514.9671 528.8537 562.5519 510.9445 536.7252 552.0922 512.9368 516.9173 527.4993 552.7326 515.9198 525.2321
worst 540.3655 520.8979 567.6569 594.5714 545.3806 583.5143 587.2286 540.7974 524.6775 540.5986 570.6416 542.783 537.0252
std 14.40665 2.916079 20.38514 17.75947 16.24505 19.95166 15.19038 12.38441 3.301751 5.610836 8.573295 12.1854 4.905863
median 516.4311 517.9106 546.5084 578.2025 520.1356 550.8402 561.0172 518.4101 519.7334 531.2967 554.225 534.326 532.1407
rank 2 1 9 13 5 10 12 4 3 8 11 7 6
C17-F6 mean 600.0008 600.8465 618.7414 644.0479 623.8526 629.3204 637.3912 601.3458 600.1938 606.3029 618.6179 602.4556 607.4921
best 600.0001 600.0026 617.6546 640.5716 614.9259 618.7987 627.5706 600.5279 600.1227 604.6819 603.1557 600.4931 605.6483
worst 600.0024 601.6626 621.5024 648.6505 631.2704 638.4976 643.6766 603.0893 600.3623 607.7053 639.1099 603.3747 608.445
std 0.001059 0.916838 1.846013 3.630547 6.802204 9.123253 7.55601 1.179296 0.113824 1.335779 16.6334 1.356157 1.252703
median 600.0003 600.8604 617.9043 643.4847 624.607 629.9926 639.1589 600.8831 600.145 606.4122 616.1031 602.9772 607.9374
rank 1 3 9 13 10 11 12 4 2 6 8 5 7
C17-F7 mean 714.9232 735.8553 770.0335 812.0262 723.6362 794.4765 804.2404 738.9214 737.1898 748.3656 736.1961 736.6172 742.9681
best 712.7689 717.4734 746.6222 797.7337 720.2506 781.8441 778.6661 731.8761 720.4588 742.0222 717.1787 725.272 732.2879
worst 716.4969 759.7501 800.0727 825.7699 726.113 805.1441 842.8269 754.0978 752.0498 753.5933 757.0473 753.4337 750.6899
std 1.562194 17.9943 24.60583 13.16748 2.810547 11.91296 28.10275 10.33946 12.94484 5.913658 19.72524 12.12503 8.93704
median 715.2135 733.0988 766.7196 812.3006 724.0905 795.4589 797.7343 734.8559 738.1253 748.9235 735.2791 733.8816 744.4474
rank 1 3 10 13 2 11 12 7 6 9 4 5 8
C17-F8 mean 816.6276 821.1931 833.5798 858.0199 815.9157 847.5389 838.4987 817.1652 815.6853 831.6274 821.3916 822.884 820.143
best 803.9798 805.9698 821.8891 845.8319 805.9698 837.1798 816.4064 812.9367 814.2627 821.404 812.9345 817.9092 811.2669
worst 851.586 853.9211 850.7427 863.7385 827.5538 854.4324 852.3891 821.8906 819.3457 842.065 829.8487 836.8133 827.5287
std 23.31975 22.21323 12.1958 8.256772 11.06309 7.741079 15.84329 3.666664 2.45444 9.1537 7.197692 9.298061 7.809856
median 805.4723 812.4407 830.8436 861.2546 815.0695 849.2718 842.5997 816.9166 814.5663 831.5204 821.3916 818.4067 820.8881
rank 3 6 10 13 2 12 11 4 1 9 7 8 5
C17-F9 mean 900.3851 929.3131 1211.93 1514.186 900 1458.039 1265.415 900.2293 965.985 941.6624 900 1084.117 905.2287
best 900.015 900.0012 958.169 1410.468 900 990.2664 1008.524 900.0018 900.5441 913.7529 900 900.9737 901.4811
worst 901.011 971.5927 1724.097 1663.035 900 2444.594 1578.136 900.9101 1155.325 980.4159 900 1338.977 907.1148
std 0.471982 34.89239 354.9109 107.5417 2.05 × 10−8 667.1913 251.4761 0.453875 126.2692 28.21168 0 216.6576 2.557814
median 900.2572 922.8293 1082.726 1491.62 900 1198.649 1237.501 900.0026 904.0356 936.2405 900 1048.258 906.1594
rank 4 6 10 13 2 12 11 3 8 7 1 9 5
C17-F10 mean 1136.471 1525.5 1833.3 2692.02 1398.269 2196.056 1831.813 1696.621 1618.109 2333.778 2369.988 1799.815 1931.023
best 1015.317 1118.755 1517.483 2508.239 1269.37 1628.727 1611.271 1431.721 1460.399 2172.52 2069.602 1548.165 1789.372
worst 1269.761 2173.755 2515.046 3078.344 1458.036 2789.958 1998.959 2038.82 1803.231 2471.171 2484.022 2102.943 2091.463
std 104.1524 455.0288 468.3656 265.2632 87.62248 516.1888 161.4886 255.5049 164.4428 130.9142 200.6485 289.059 126.6268
median 1130.404 1404.745 1650.336 2590.748 1432.834 2182.769 1858.51 1657.972 1604.402 2345.711 2463.163 1774.075 1921.627
rank 1 3 8 13 2 10 7 5 4 11 12 6 9
C17-F11 mean 1110.292 1124.026 1151.953 4189.355 1101.74 2433.766 1222.852 1122.666 1125.431 1164.599 1141.981 1160.628 1626.893
best 1106.88 1117.954 1118.262 1484.117 1100.601 1175.783 1164.024 1105.305 1113.134 1157.099 1121.042 1117.92 1359.157
worst 1113.47 1133.078 1209.026 6861.324 1103.787 5818.316 1345.834 1135.827 1132.354 1175.083 1173.496 1208.451 1865.215
std 2.815898 6.45982 39.95022 2416.697 1.417748 2258.972 83.82071 12.94547 8.869157 8.65636 22.38728 42.52562 221.4175
median 1110.408 1122.536 1140.263 4205.989 1101.286 1370.483 1190.775 1124.767 1128.117 1163.106 1136.692 1158.07 1641.6
rank 2 4 7 13 1 12 10 3 5 9 6 8 11
C17-F12 mean 1242.422 2343.334 1,181,918 7.58 × 108 1233.441 1096,381 4,964,945 370,327 756,766.5 3,736,063 1,095,779 5930.549 913,806.8
best 1207.99 1359.837 382,250 1.68 × 108 1200.822 38,588.44 1,889,170 17,106.39 235,233.1 616,984.9 509,541 2404.891 132,160.6
worst 1330.82 4297.499 2,143,478 1.32 × 109 1320.289 2,832,543 10,251,735 674,113.1 1,939,197 5,876,192 1,853,207 11,438.52 2,872,053
std 59.08526 1323.889 823,784.1 5.85 × 108 58.10221 1,238,741 3,677,451 314,405.5 801,178.8 2,473,613 568,776.2 4251.026 1,315,343
median 1215.439 1858 1,100,971 7.69E × 108 1206.327 757,195.4 3,859,438 395,044.3 426,317.8 4,225,537 1,010,183 4939.391 325,507
rank 2 3 10 13 1 9 12 5 6 11 8 4 7
C17-F13 mean 1314.651 1329.426 19,590.41 36,919,805 1306.198 7713.778 17,906.98 6218.485 11,600.44 10,709.37 10,719.01 9477.394 14,731.63
best 1308.406 1314.537 2827.835 3,065,090 1301.331 5119.752 2690.152 1643.858 7514.508 3941.49 5323.606 2204.365 8697.185
worst 1318.079 1363.912 33,636.44 1.23 × 108 1310.414 11,977.73 34,896.49 18,348.49 14,579.42 17,269.75 15,137.13 16,209.74 22,062.2
std 4.420181 23.19983 15,927.29 57,222,140 4.14073 3006.084 15,038.52 8095.684 3088.611 5648.28 4147.954 5798.845 5591.951
median 1316.06 1319.628 20,948.69 11,023,424 1306.523 6878.815 17,020.65 2440.796 12,153.91 10,813.12 11,207.65 9747.735 14,083.57
rank 2 3 12 13 1 5 11 4 9 7 8 6 10
C17-F14 mean 1414.72 1423.19 2068.49 5643.20 1404.48 3501.69 3400.44 1493.75 4803.04 1568.78 5878.19 5869.60 5357.57
best 1412.45 1406.97 1699.95 4926.75 1401.00 1.55 × 103 1648.11 1.4 × 103 4050 1522.97 4842 2264 2517.23
worst 1419.77 1435.92 2935.30 7310.20 1406.97 5.45 × 103 5862.66 1551 5156 1652.01 8015.69 7283 8985.62
std 3.390648 12.24421 582.1813 1119.612 2.50 2.21 × 103 2049.513 5 510.9601 59.87624 1.49 × 103 2.41 × 103 2913.649
median 1413.33 1424.93 1819.36 5167.92 1404.98 3.50 × 103 3.05 × 103 1.49 × 103 5002.87 1550.06 5327.38 6965.79 4963.72
rank 2 3 6 11 1 8 7 4 9 5 13 12 10
C17-F15 mean 1512.83 1521.97 5583.05 14,802.85 1500.96 7545.17 5337.48 1861.61 3291.73 1839.96 25,559.97 4109.45 5985.44
best 1511.37 1511.68 2115.43 2826.68 1500.28 1.68 × 103 2420.26 1.54 × 103 1575 1690.59 11,956 1622 3545.59
worst 1514.98 1528.08 13,461.88 32,524.72 1502.00 2.09 × 104 6967.84 2255 7770 1979.28 38,417.80 6877 8873.14
std 1.654731 7.536983 5293.321 12967.07 0.79 9.04 × 103 2099.34 3.67 × 102 2997.628 147.988 1.26 × 104 2.55 × 103 2702.172
median 1512.50 1524.07 3377.44 11,930.01 1500.79 3.80 × 103 5.98 × 103 1.82 × 103 1911.17 1844.99 25,932.99 3968.99 5761.51
rank 2 3 9 12 1 11 8 5 6 4 13 7 10
C17-F16 mean 1611.84 1631.96 1825.20 2047.53 1601.43 1939.80 1958.00 1810.13 1816.18 1764.56 2108.53 1936.44 1791.70
best 1607.70 1602.02 1645.36 1835.70 1600.83 1.80 × 103 1845.63 1.61 × 103 1668 1673.94 1973 1842 1728.99
worst 1615.65 1719.59 1950.57 2341.89 1601.90 2.06 × 103 2123.07 2107 1990 1899.69 2317.95 2037 1848.57
std 3.460903 58.42219 128.574 213.7822 0.44 1.30 × 102 120.1071 2.10 × 102 140.4967 99.39318 1.57 × 102 87.4 64.59923
median 1612.00 1603.12 1852.44 2006.27 1601.49 1.95 × 103 1.93 × 103 1.76 × 103 1803.64 1742.32 2071.58 1933.46 1794.62
rank 2 3 8 12 1 10 11 6 7 4 13 9 5
C17-F17 mean 1716.703 1738.518 1754.813 1827.274 1703.13 2030.624 1805.698 1769.854 1764.037 1782.169 1857.806 1788.933 1757.909
best 1713.768 1710.808 1736.971 1809.096 1701.435 1769.61 1767.831 1723.549 1722.862 1769.332 1751.548 1742.054 1746.479
worst 1719.172 1753.339 1802.155 1837.197 1704.773 2407.068 1821.411 1790.076 1797.933 1799.261 1993.65 1864.424 1765.935
std 2.329847 18.92729 31.64484 12.48988 1.416707 307.1122 25.48385 31.13371 38.49878 15.20238 123.4642 55.24992 8.187043
median 1716.937 1744.963 1740.062 1831.402 1703.157 1972.91 1816.775 1782.896 1767.677 1780.042 1843.013 1774.627 1759.61
rank 2 3 4 11 1 13 10 7 6 8 12 9 5
C17-F18 mean 1814.405 1821.362 12,583.12 6,109,172 1801.274 23,279.35 12,052.7 31,257.28 15,733.45 32,735.85 10,284.31 6716.702 11,959.11
best 1810.809 1808.227 5064.639 302,305.5 1800.582 14,032.49 6236.408 7496.333 2186.154 13,630.19 6724.069 4646.373 3903.202
worst 1819.123 1830.204 16,593.21 17,734,831 1801.954 36,612.74 20,512.16 46,205.61 35,629.02 48,828.46 12,582.88 11,176.9 33,403.2
std 3.560254 10.39659 5168.715 8,077,112 0.638221 9630.484 6341.297 16,873.78 14,345.79 15,253.63 2500.631 3067.479 14,314.21
median 1813.843 1823.509 14,337.31 3,199,777 1801.279 21,236.09 10,731.12 35,663.58 12,559.31 34,242.38 10,915.15 5521.766 5265.028
rank 2 3 8 13 1 10 7 11 9 12 5 4 6
C17-F19 mean 1900.829 1906.001 7055.795 754,594.9 1988.096 7862.419 11,722.22 1924.021 3422.268 2919.764 43,205.63 12,423.58 8045.107
best 1900.197 1902.859 2196.819 48,985.81 1941.345 1936.761 2247.991 1904.848 1931.079 2082.118 11,768.13 1992.972 2511.267
worst 1901.132 1911.477 14,063.29 1621,173 2033.869 14,054.72 35,401.61 1943.471 7740.098 5097.511 62,729.71 32,949.66 13,550.94
std 0.426417 4.051826 5770.348 709,246.5 37.97119 6845.286 15,850.82 15.98525 2879.051 1456.032 22,823.33 14,370.32 5195.004
median 1900.994 1904.834 5981.538 674,110.5 1988.585 7729.098 4619.639 1923.882 2008.947 2249.714 49,162.35 7375.847 8059.112
rank 1 2 7 13 4 8 10 3 6 5 12 11 9
C17-F20 mean 2011.485 2042.536 2182.848 2239.101 2108.71 2113.828 2117.662 2049.031 2069.477 2103.812 2271.99 2148.104 2046.167
best 2003.98 2020.622 2033.57 2176.378 2029.565 2032.586 2074.137 2023.77 2040.489 2070.52 2201.309 2086.369 2040.594
worst 2024.81 2065.244 2315.735 2298.524 2143.217 2186.926 2165.246 2088.018 2141.267 2190.885 2371.812 2206.599 2054.028
std 9.604069 23.49206 126.9386 60.11148 53.07689 71.16499 38.70398 30.47418 48.05391 58.21754 82.95245 49.2503 6.047881
median 2008.575 2042.138 2191.043 2240.75 2131.029 2117.899 2115.632 2042.168 2048.075 2076.922 2257.419 2149.723 2045.023
rank 1 2 11 12 7 8 9 4 5 6 13 10 3
C17-F21 mean 2200 2257.378 2214.815 2272.021 2285.241 2370.129 2286.841 2318.856 2316.059 2333.48 2380.593 2298.441 2248.355
best 2200 2201.776 2204.429 2225.704 2256.272 2357.389 2208.473 2312.628 2314.555 2320.683 2361.841 2202.641 2211.672
worst 2200 2315.502 2241.859 2298.356 2313.686 2395.748 2352.572 2328.8 2317.369 2339.95 2399.185 2341.226 2334.061
std 4.36 × 10−6 63.34808 18.08569 32.13155 30.34504 17.75696 74.57407 7.057306 1.33189 8.678521 15.60657 64.84178 57.45861
median 2200 2256.116 2206.485 2282.012 2285.503 2363.69 2293.16 2316.999 2316.157 2336.644 2380.674 2324.948 2223.844
rank 1 4 2 5 6 12 7 10 9 11 13 8 3
C17-F22 mean 2293.452 2304.053 2309.64 2961.228 2300.478 2852.928 2310.94 2447.659 2303.451 2323.176 2300 2590.674 2315.89
best 2249.619 2302.865 2304.685 2736.917 2300.289 2325.93 2306.026 2303.655 2301.229 2317.806 2300 2301.37 2312.981
worst 2309.573 2306.702 2311.968 3125.843 2300.639 4289.031 2315.364 2876.013 2308.429 2330.145 2300 3455.61 2322.759
std 29.29682 1.78132 3.347251 163.7741 0.148633 958.3573 3.841076 285.5712 3.34564 5.128153 4.79 × 10−11 576.6258 4.631892
median 2307.308 2303.322 2310.953 2991.077 2300.493 2398.375 2311.184 2305.484 2302.074 2322.376 2300 2302.858 2313.91
rank 1 5 6 13 3 12 7 10 4 9 2 11 8
C17-F23 mean 2610.573 2629.183 2645.231 2708.158 2612.224 2726.841 2653.024 2616.866 2616.438 2639.373 2806.265 2640.991 2667.811
best 2607.664 2617.394 2632.674 2676.838 2606.93 2674.586 2628.832 2605.735 2605.898 2633.039 2736.331 2624.248 2659.715
worst 2612.054 2640.741 2664.384 2751.868 2615.963 2799.207 2684.875 2626.638 2621.972 2644.202 2955.197 2656.69 2674.554
std 1.994539 10.55426 14.9135 35.0647 4.480225 56.75694 23.83249 9.040098 7.270681 5.590693 102.8952 14.70599 7.17143
median 2611.287 2629.299 2641.933 2701.962 2613.002 2716.785 2649.195 2617.545 2618.941 2640.125 2766.766 2641.513 2668.487
rank 1 5 8 11 2 12 9 4 3 6 13 7 10
C17-F24 mean 2500 2628.429 2777.971 2866.473 2569.191 2809.687 2721.283 2747.647 2747.38 2702.715 2798.085 2766.089 2796.904
best 2500 2500.026 2749.551 2831.736 2500 2788.515 2539.368 2741.391 2733.965 2519.228 2667.104 2743.202 2777.411
worst 2500 2756.728 2810.839 2925.445 2644.684 2842.916 2793.127 2760.786 2763.043 2765.55 2910.085 2813.42 2837.744
std 0.000138 148.1166 27.63919 40.74193 59.26318 24.23185 121.6661 8.946334 13.17159 122.3327 99.80776 31.95768 28.33329
median 2500 2628.481 2775.747 2854.356 2566.041 2803.659 2776.318 2744.206 2746.256 2763.041 2807.575 2753.866 2786.23
rank 1 3 9 13 2 12 5 7 6 4 11 8 10
C17-F25 mean 2906.512 2922.277 2912.059 3302.497 2897.744 3106.26 2952.732 2944.896 2936.407 2928.564 2921.498 2929.4 2955.349
best 2899.622 2897.934 2899.173 3227.936 2897.743 2996.274 2950.071 2943.625 2913.914 2903.231 2899.585 2899.585 2949.724
worst 2914.472 2946.585 2949.468 3386.778 2897.746 3238.662 2957.737 2946.057 2946.069 2950.815 2943.426 2950.481 2961.557
std 7.989653 27.1567 24.94164 65.75238 0.001401 109.1914 3.436649 1.280875 15.0943 24.7158 25.30253 22.9263 4.8434
median 2905.976 2922.294 2899.797 3297.637 2897.743 3095.053 2951.561 2944.951 2942.823 2930.105 2921.49 2933.766 2955.059
rank 2 5 3 13 1 12 10 9 8 6 4 7 11
C17-F26 mean 2671.195 2913.423 2985.864 3820.788 2675.001 3616.499 3543.485 2894.319 3162.049 3024.196 3934.065 2953.575 2984.157
best 2617.932 2817.326 2800 3472.539 2600.001 3138.702 3155.692 2801.236 2817.027 2962.221 2800 2900 2918.692
worst 2822.654 3035.347 3176.148 4183.224 2900 4076.951 3938.706 2975.736 3958.769 3149.034 4458.174 3043.137 3058.781
std 100.9928 90.24848 214.6477 306.4302 149.9997 384.0996 344.4273 71.55693 534.9178 84.63646 768.3315 68.48644 71.71749
median 2622.096 2900.509 2983.654 3813.695 2600.001 3625.172 3539.772 2900.152 2936.199 2992.764 4239.043 2935.581 2979.577
rank 1 4 7 12 2 11 10 3 9 8 13 5 6
C17-F27 mean 3089.249 3108.049 3122.299 3241.788 3230.617 3156.931 3131.995 3128.978 3112.27 3107.927 3236.309 3104.619 3158.594
best 3088.978 3097.47 3095.743 3130.053 3089.518 3099.004 3100.639 3089.735 3094.181 3094.735 3223.231 3096.887 3110.429
worst 3089.518 3119.426 3187.808 3448.33 3302.844 3201.841 3212.034 3245.764 3138.824 3143.478 3259.486 3115.015 3195.857
std 0.310716 9.908994 43.79996 141.0072 97.5953 51.24289 53.52643 77.85813 20.82847 23.73436 16.13351 7.657847 36.95242
median 3089.25 3107.651 3102.823 3194.385 3265.053 3163.44 3107.654 3090.206 3108.038 3096.747 3231.259 3103.287 3164.045
rank 1 4 6 13 11 9 8 7 5 3 12 2 10
C17-F28 mean 3100 3206.371 3298.81 3829.484 3216.221 3436.214 3311.827 3335.937 3320.677 3445.166 3476.706 3368.271 3180.566
best 3100 3101.23 3172.905 3741.083 3100 3216.368 3185.855 3164.423 3227.504 3224.747 3462.464 3239.91 3150.246
worst 3100 3383.883 3411.822 3893.295 3283.338 3554.863 3436.561 3411.825 3433.953 3731.813 3496.499 3446.48 3250.807
std 7.13 × 10−5 125.1841 97.91492 70.64911 81.82053 153.671 130.6719 115.1056 103.9361 210.5104 15.77081 89.50779 47.68498
median 3100 3170.186 3305.256 3841.779 3240.773 3486.812 3312.445 3383.749 3310.626 3412.052 3473.932 3393.348 3160.605
rank 1 3 5 13 4 10 6 8 7 11 12 9 2
C17-F29 mean 3138.606 3179.875 3296.049 3393.557 3289.561 3381.154 3360.139 3232.25 3245.584 3197.841 3362.024 3221.345 3231.314
best 3131.359 3164.605 3216.476 3316.959 3206.422 3329.678 3226.82 3135.375 3159.205 3187.325 3241.182 3171.9 3222.514
worst 3148.378 3205.527 3382.815 3465.973 3346.892 3413.532 3430.368 3320.002 3367.448 3209.226 3673.067 3259.484 3241.71
std 7.707765 18.65754 85.63264 76.78127 60.23812 39.15099 91.66353 86.28562 90.14385 11.73545 208.2333 37.86476 8.061759
median 3137.343 3174.685 3292.453 3395.648 3302.466 3390.704 3391.683 3236.811 3227.843 3197.407 3266.924 3226.999 3230.516
rank 1 2 9 13 8 12 10 6 7 3 11 4 5
C17-F30 mean 3396.648 7103.166 315,325.2 3,935,476 3593.41 228,769.3 1854,829 18,378.17 25,404.81 328,679.2 837,788.8 434,361.7 2254,186
best 3395.218 4030.14 111,836.1 885,863.3 3485.918 9138.959 207,480.4 6468.614 10,065.88 44,946.47 644,043.4 5474.912 282,133.6
worst 3397.324 15,735.06 821,835.5 6,216,163 3634.301 458,333.2 5,681,033 35,678.41 34,710.86 821,511 1069,950 1,705,095 4,266,383
std 0.972309 5757.626 338,593.4 2,231,806 71.81478 185,592.7 2,567,825 12,749.49 11,597.43 352,907.1 176,988.7 847,168.3 1,783,824
median 3397.024 4323.731 163,814.6 4,319,938 3626.71 223,802.5 765,402.1 15,682.84 28,421.26 224,129.6 818,581 13,438.71 2,234,113
rank 1 3 7 13 2 6 11 4 5 8 10 9 12
Sum rank 46 106 215 356 87 303 272 160 182 218 265 206 223
Mean rank 1.586207 3.655172 7.413793 12.27586 3 10.44828 9.37931 5.517241 6.275862 7.517241 9.137931 7.103448 7.689655
Total rank 1 3 7 13 2 12 11 4 5 8 10 6 9

Table 3.

Optimization results of the CEC 2017 test suite (for the dimension d=30).

SOA WSO AVOA RSA MPA TSA WOA MVO GWO TLBO GSA PSO GA
C17-F1 mean 1575.134 8.63 × 109 3318.344 4.38 × 1010 44,342.91 2.31 × 1010 2.19 × 109 660,553.8 2.3 × 109 6.17 × 109 11,193,471 2 × 109 1.32 × 108
best 291.5791 3.2 × 109 301.9834 3.91 × 1010 23,422.06 1.8 × 1010 1.14 × 109 489,540.5 1.48 × 109 5.57 × 109 2775.087 5373.926 84,091,185
worst 2723.003 1.55 × 1010 8149.68 5.39 × 1010 73,308.85 2.69 × 1010 4.06 × 109 1,043,985 3.25 × 109 7.22 × 109 39,077,336 6.32 × 109 2.15 × 108
std 1312.344 5.69 × 109 3675.955 6.83 × 109 23,716.31 3.78 × 109 1.36 × 109 257,939.3 7.37 × 108 7.68 × 108 18,781,636 2.98 × 109 57,126,045
median 1642.976 7.91 × 109 2410.857 4.11 × 1010 40,320.37 2.38 × 1010 1.77 × 109 554,344.8 2.24 × 109 5.95 × 109 2,846,886 8.4 × 108 1.15 × 108
rank 1 11 2 13 3 12 8 4 9 10 5 7 6
C17-F3 mean 781.8758 42,375.1 47,609.78 78,405.91 834.2454 48,537.76 225,225.5 1031.676 55,393.14 36,906.86 102,114.9 77,694.12 134,031.2
best 470.0985 31,992.7 25,840.42 60,713.72 466.3567 36,205.28 165,937.7 751.8445 42,537.2 28,114.76 87,911.84 5616.74 91,331.46
worst 1159.523 56,799.39 61,573.93 85,173.33 1251.796 60,139.23 339,833.4 1377.855 69,178.02 44,671.67 112,455.1 122,259.2 171,056.6
std 363.8149 11,011.05 15,321.68 11,832.89 426.2832 11,184.08 79,056.19 259.0859 14,094.56 8186.672 11,070.13 52,140.19 33,150.42
median 748.9407 40,354.16 51,512.39 83,868.3 809.4147 48,903.27 197,565.4 998.5019 54,928.67 37,420.51 104,046.4 91,450.26 136,868.4
rank 1 5 6 10 2 7 13 3 8 4 11 9 12
C17-F4 mean 481.8263 841.7389 518.3661 10,440.38 495.7528 2158.726 841.9903 495.544 567.0971 827.2028 603.7402 504.0106 813.8432
best 469.5735 740.4671 494.0059 6680.906 482.257 1388.877 664.6617 488.5097 532.196 630.1235 582.046 478.9838 724.672
worst 496.1271 1012.754 537.7292 14,606.03 517.0849 2948.487 1220.665 504.9644 623.5882 1298.773 628.6736 536.8896 894.6409
std 12.21788 127.7259 18.14231 3289.65 15.86538 664.9026 255.0823 7.418566 39.35261 316.7743 20.33317 24.07526 71.3288
median 480.8022 806.8675 520.8646 10237.29 491.8346 2148.769 741.317 494.3509 556.3021 689.9572 602.1205 500.0845 818.03
rank 1 10 5 13 3 12 11 2 6 9 7 4 8
C17-F5 mean 591.9605 653.5151 740.563 909.9791 604.5444 853.4376 764.4085 616.2858 623.7568 746.731 737.7933 685.3203 706.2255
best 572.8715 603.0483 700.9927 881.9704 597.5869 831.9647 737.6831 577.9794 610.044 696.6675 716.8998 620.4016 695.0019
worst 609.7335 691.464 803.4606 946.4631 612.4978 888.9031 787.6346 671.5395 645.0115 779.7375 765.6516 768.6397 714.7736
std 17.43398 39.32124 46.32888 30.80919 6.734852 24.70772 24.55298 39.50365 15.98556 36.95873 21.72216 61.70543 9.752587
median 592.6185 659.7741 728.8994 905.7414 604.0464 846.4413 766.1582 607.8121 619.9859 755.2595 734.3109 676.12 707.5632
rank 1 5 9 13 2 12 11 3 4 10 8 6 7
C17-F6 mean 606.6229 644.2901 649.6843 688.3251 603.2172 667.3338 677.7711 623.4261 610.7615 641.7919 660.113 650.2099 640.5046
best 605.5854 639.7766 647.5717 682.6749 601.8096 648.0678 656.5877 605.7405 604.005 636.0484 659.3197 643.6113 632.6248
worst 608.634 653.2473 652.9881 695.4187 605.8092 682.7658 699.2122 638.1243 616.1276 646.9417 661.167 664.0501 649.3386
std 1.435549 6.086035 2.340959 5.885883 1.859946 16.20593 17.91275 14.59694 5.139016 4.469085 0.814301 9.348912 7.046186
median 606.1361 642.0682 649.0887 687.6034 602.6249 669.2509 677.6422 624.9199 611.4567 642.0888 659.9828 646.5891 640.0274
rank 2 7 8 13 1 11 12 4 3 6 10 9 5
C17-F7 mean 824.4019 1028.891 1173.837 1378.659 871.1627 1261.634 1237.611 877.7531 902.3727 1050.815 987.1371 961.4578 998.7671
best 808.2562 937.0001 1050.146 1364.064 830.9612 1217.349 1191.509 830.7576 869.2935 1023.079 936.652 940.4088 990.4792
worst 840.1661 1166.637 1346.571 1403.463 963.2763 1286.653 1300.094 923.0444 952.51 1093.22 1062.44 991.3926 1006.751
std 15.87142 97.43161 130.9887 17.50672 62.07233 30.40281 53.17939 38.72923 40.18853 33.72067 55.15938 24.88631 6.666849
median 824.5927 1005.964 1149.315 1373.554 845.2067 1271.267 1229.42 878.6053 893.8436 1043.48 974.7284 957.015 998.9192
rank 1 8 10 13 2 12 11 3 4 9 6 5 7
C17-F8 mean 876.44 921.3526 959.7397 1143.549 905.3425 1109.568 1022.72 918.4966 931.9204 1052.634 972.3755 928.3456 1000.158
best 861.6931 896.2341 927.3542 1121.49 882.7297 1050.063 974.1633 894.9188 904.3727 1014.92 946.2582 899.4956 989.1129
worst 901.5509 949.9888 983.0733 1172.767 930.5994 1173.263 1072.325 929.7411 960.3594 1079.362 1000.98 953.2309 1019.463
std 18.96082 22.04258 25.26299 25.97783 22.14314 51.04285 42.15311 16.41749 25.40171 27.15429 24.10391 23.49774 13.27682
median 871.258 919.5937 964.2657 1139.97 904.0204 1107.473 1022.196 924.6632 931.4748 1058.127 971.1318 930.3279 996.027
rank 1 4 7 13 2 12 10 3 6 11 8 5 9
C17-F9 mean 1195.591 6940.902 5082.067 11,265.22 1229.29 14,700.33 12,240.59 3886.39 2149.413 4773.832 4288.668 4170.381 1390.886
best 1005.433 5371.93 3739.922 10,986.11 1039.082 12,687.95 8790.439 2585.385 1625.875 4462.957 3715.719 1685.736 1257.047
worst 1413.609 9175.404 5799.199 11,406.53 1446.192 17,328.07 16,223.67 6664.175 2800.198 5128.325 5171.329 6392.186 1505.439
std 174.8498 1601.414 921.6272 189.314 172.3628 2274.191 3233.82 1919.637 510.5671 310.8324 641.2085 1950.664 125.7143
median 1181.661 6608.138 5394.574 11,334.13 1215.943 14,392.65 11,974.14 3148 2085.789 4752.023 4133.811 4301.802 1400.529
rank 1 10 9 11 2 13 12 5 4 8 7 6 3
C17-F10 mean 3816.318 5075.775 5669.471 8287.882 4220.886 7602.726 6780.741 5112.877 4492.313 8516.982 5023.915 5002.451 6061.83
best 3461.682 4293.963 4863.102 7401.561 3924.042 6749.686 6256.547 4322.227 3596.22 8229.134 4753.717 4206.05 5451.612
worst 4025.525 6408.048 6213.965 8953.203 4725.856 8093.557 7076.522 6028.47 5426.175 8698.705 5457.712 5740.762 6971.01
std 268.2071 933.6489 647.4401 649.1055 362.4291 596.9208 382.085 785.8896 962.8636 207.2443 323.6773 627.4781 645.3234
median 3889.033 4800.545 5800.408 8398.382 4116.823 7783.83 6894.948 5050.406 4473.429 8570.044 4942.116 5031.496 5912.35
rank 1 6 8 12 2 11 10 7 3 13 5 4 9
C17-F11 mean 1162.133 1448.116 1268.696 9328.214 1171.813 5380.791 6344.694 1341.146 1947.539 1897.276 3021.119 1401.099 5138.217
best 1142.585 1297.005 1196.704 7579.907 1132.01 3668.83 4242.53 1265.451 1440.926 1744.854 2320.74 1164.748 1545.325
worst 1182.493 1551.242 1337.29 10,508.06 1215.997 6958.553 9436.31 1429.885 2921.548 2074.605 3738.218 1770.983 9100.655
std 18.852 121.068 58.60946 1341.609 41.78269 1638.069 2277.368 82.79307 687.1649 140.7209 668.1668 268.493 3518.582
median 1161.728 1472.108 1270.394 9612.443 1169.622 5447.89 5849.969 1334.624 1713.841 1884.822 3012.758 1334.332 4953.445
rank 1 6 3 13 2 11 12 4 8 7 9 5 10
C17-F12 mean 90,577.25 85,200,129 22,294,766 1.17 × 1010 90,003.89 4.13 × 109 1.9 × 108 16,023,229 30,541,462 3.65 × 108 2.13 × 108 436,028.7 7,615,346
best 53,334.11 6,278,481 3,137,139 1.04 × 1010 53,008.9 8.42 × 108 54,166,306 1969,767 2402,615 2.99 × 108 41,143,265 236,773 5,611,464
worst 186,847.7 1.92 × 108 54,450,458 1.47 × 1010 185,636.8 9.43 × 109 3.02 × 108 27,669,712 90,151,780 4.98 × 108 6.8 × 108 912,580.8 9,655,726
std 64,578.16 77,647,077 22,587,307 2.04 × 109 64,148.09 3.69 × 109 1.08 × 108 10,686,736 40,183,994 90,619,476 3.12 × 108 320,014.9 1,658,891
median 61,063.6 71,256,869 15,795,734 1.08 × 1010 60,684.91 3.12 × 109 2.03 × 108 17,226,719 14,805,726 3.3 × 108 65,228,755 297,380.4 7,597,098
rank 2 8 6 13 1 12 9 5 7 11 10 3 4
C17-F13 mean 1698.702 42,943.25 159,812.1 1.13 × 1010 1687.016 3.08 × 109 1880,155 115,014 806,958.5 50,671,827 38,902.02 19,073,995 8,631,128
best 1666.692 15,453.39 88,435.66 5.92 × 109 1655.899 3.01 × 108 874,962.7 43,649.1 90,835.15 24,346,775 31,538.43 10,348.01 5,437,187
worst 1739.004 69,114.37 252,818.6 1.38 × 1010 1727.879 4.75 × 109 3,971,612 152,301.5 2,153,200 79,648,604 56,967.6 71,682,069 11,994,455
std 30.25763 29,451.87 68,264.23 3.62 × 109 30.04096 1.98 × 109 1,425,344 48,532.06 945,863.6 22,741,505 12,177.81 35,135,804 2,736,987
median 1694.557 43,602.61 148,997.1 1.27 × 1010 1682.144 3.64 × 109 1,337,022 132,052.8 491,899.7 49,345,965 33,551.03 2,301,781 8,546,436
rank 2 4 6 13 1 12 8 5 7 11 3 10 9
C17-F14 mean 1444.401 1676.266 289,413.4 2,344,304 1496.974 605,895.5 4,052,315 31,475.33 80,820.24 125,817.1 1220,811 40,538.98 1389,524
best 1432.619 1509.528 40,389.43 1,178,223 1482.994 19,646.14 500,090.9 1774.484 3031.162 56,550.37 792,133.3 5098.106 79,752
worst 1454.965 1968.988 670,169.8 3,490,954 1528.7 2,259,238 10,915,286 81,318.86 304,629.3 166,885.1 1843,312 113,632 2,018,125
std 9.363157 205.8048 277,873.9 1,112,536 21.28861 1,102,518 4,662,123 34,996.97 149,234.9 51,967.8 494,689.9 49,872.43 884,978.4
median 1445.009 1613.274 223,547.2 2,354,020 1488.101 72,349.17 2,396,942 21,403.99 7810.246 139,916.5 1,123,899 21,712.91 1,730,110
rank 1 3 8 12 2 9 13 4 6 7 10 5 11
C17-F15 mean 1607.963 4778.296 39,852.03 6.38 × 108 1689.005 11,487,233 2179,861 42,062.9 55,302.7 6330,079 17,042.7 22,342.61 1,660,817
best 1597.136 2049.811 11,559.75 5.5 × 108 1662.636 510,798.9 41,148.44 27,984.36 29,781.28 1782,675 12,076.24 9161.007 162,991.5
worst 1620.23 7380.576 64,784.18 7.04 × 108 1713.512 30,936,722 6697,059 53,948.33 95,876.74 10,145,977 23,149.44 43,566.9 2,552,150
std 11.79297 2216.528 22,477.62 75,373,693 26.43209 14,324,358 3053,330 10,716.84 28,402.06 3805,854 4629.296 16,392.76 1,046,225
median 1607.243 4841.398 41532.1 6.48 × 108 1689.935 7,250,705 990,617.7 43,159.45 47,776.39 6,695,832 16,472.57 18,321.27 1,964,064
rank 1 3 6 13 2 12 10 7 8 11 4 5 9
C17-F16 mean 1938.024 2652.321 3090.893 5197.758 2043.515 3941.647 3856.78 2718.081 2844.053 3652.155 3800.762 2579.706 2881.999
best 1875.092 2467.942 2618.661 4355.175 1960.684 2696.154 3503.463 2471.407 2350.898 2855.694 3606.06 2182.495 2536.668
worst 2022.866 2873.364 3646.496 5943.335 2140.407 5949.276 4712.045 3124.71 3696.224 4147.742 3977.124 3007.692 3235.006
std 63.16545 180.599 422.6948 848.5357 76.10694 1411.044 573.5086 297.6959 587.7307 555.942 165.3951 348.332 306.3028
median 1927.069 2633.988 3049.207 5246.261 2036.484 3560.579 3605.805 2638.104 2664.545 3802.591 3809.932 2564.319 2878.16
rank 1 4 8 13 2 12 11 5 6 9 10 3 7
C17-F17 mean 1852.902 2208.309 2527.865 3850.265 1842.558 3293.211 2983.695 2140.944 2036.312 2268.715 2581.32 2297.254 2189.114
best 1788.722 2004.347 2371.871 3442.105 1779.719 2060.002 2607.115 2039.798 1924.983 2092.269 2474.207 2111.585 2010.935
worst 1928.103 2579.523 2652.707 4571.363 1922.001 5754.239 3280.496 2263.674 2223.179 2603.348 2743.277 2433.751 2310.59
std 71.09131 262.7278 122.841 511.0619 71.75205 1677.199 286.4468 106.3038 138.6211 232.8375 131.3936 136.9696 131.9916
median 1847.391 2124.683 2543.44 3693.796 1834.256 2679.302 3023.584 2130.153 1998.542 2189.622 2553.898 2321.84 2217.466
rank 2 6 9 13 1 12 11 4 3 7 10 8 5
C17-F18 mean 1938.93 73,105.14 2,825,586 34,857,872 1925.262 1277,923 12,144,452 500,241.1 1900,915 1,703,500 549,137.3 690,457.8 4,288,985
best 1893.579 35,316.23 300,783.8 11,269,502 1876.939 562,332.5 5149,402 138,664.6 227,445.9 539,938.8 307,806.8 65,741.96 1,298,945
worst 2006.212 126,012.8 5,637,821 68,482,148 1993.891 1,910,634 31,414,794 794,063.9 3,767,376 2,823,794 1,069,302 1,843,343 7,761,510
std 55.16086 43,259.8 2,501,283 24,260,902 55.11681 631,242.3 12,853,387 306,007.1 1,464,392 954,837.7 351,297.8 816,443.5 2,854,320
median 1927.964 65,545.78 2,681,870 29,839,919 1915.11 1,319,364 6,006,807 534,118 1,804,419 1,725,134 409,720.2 426,373.2 4,047,743
rank 2 3 10 13 1 7 12 4 9 8 5 6 11
C17-F19 mean 1950.448 7634.682 72,080.61 1.04 × 109 1934.536 46,099,123 16,697,045 566,616.3 776,641.6 6,505,032 87,089.66 155,575 1,002,429
best 1944.048 4603.741 15,265.2 7.54 × 108 1925.933 1968,442 1190,037 237,497.3 45,758.44 5,013,834 47,176.61 2541.803 178,602.2
worst 1956.475 9305.339 160,723 1.58 × 109 1940.446 1.4 × 108 42,887,049 962,525.9 2,874,146 8,511,539 117,244.7 526,626 2,377,684
std 6.70424 2126.603 63,361.95 3.68 × 108 6.19493 64,769,055 18,312,639 316,644.1 1,398,964 1,468,164 29,169.63 249,691.1 964,832.8
median 1950.635 8314.824 56,167.14 9.2 × 108 1935.883 21,268,185 11,355,547 533,220.9 93,330.9 6,247,378 91,968.68 46,566.05 726,714.7
rank 2 3 4 13 1 12 11 7 8 10 5 6 9
C17-F20 mean 2189.442 2360.68 2678.297 3018.944 2202.08 2907.819 2744.225 2463.574 2502.458 2699.637 3079.815 2833.366 2438.403
best 2134.196 2288.632 2510.461 2829.558 2121.756 2570.504 2403.758 2140.461 2283.051 2586.227 2680.886 2259.638 2241.364
worst 2259.836 2498.568 2933.844 3140.294 2261.922 3136.657 2907.139 2802.38 2617.604 2888.94 3587.357 3572.419 2528.431
std 57.14654 94.38145 186.4711 133.7757 60.93235 261.575 235.0817 303.3727 149.2588 136.6338 379.9235 552.2857 132.8408
median 2181.868 2327.759 2634.442 3052.963 2212.321 2962.058 2833.001 2455.727 2554.588 2661.69 3025.509 2750.703 2491.908
rank 1 3 7 12 2 11 9 5 6 8 13 10 4
C17-F21 mean 2334.267 2451.525 2451.182 2708.062 2372.321 2623.763 2600.99 2418.065 2435.549 2544.532 2590.171 2440.405 2497.362
best 2229.608 2427.241 2210.563 2624.032 2364.018 2578.473 2539.261 2385.897 2403.354 2514.163 2570.64 2423.64 2490.605
worst 2384.456 2472.696 2619.705 2807.897 2387.931 2707.121 2653.493 2460.016 2517.673 2556.921 2628.386 2466.822 2506.684
std 70.60764 20.94728 172.4367 79.98545 10.64284 58.08507 49.47883 31.62808 55.05508 20.48386 25.92502 19.61484 6.981597
median 2361.502 2453.082 2487.23 2700.16 2368.668 2604.729 2605.603 2413.174 2410.585 2553.522 2580.83 2435.579 2496.079
rank 1 7 6 13 2 12 11 3 4 9 10 5 8
C17-F22 mean 2332.529 3959.433 6059.49 8152.075 2330.163 7394.703 7190.862 6119.96 4511.888 8205.841 6631.627 4407.861 2804
best 2302.568 2653.991 2403.992 7043.939 2303.498 4181.538 3233.91 4962.584 2908.358 3396.988 4129.775 2417.459 2740.193
worst 2373.482 5235.829 7475.833 9265.812 2405.022 9991.897 9030.261 7463.774 6446.611 10,454 7731.139 7039.898 2875.878
std 35.41728 1461.304 2441.084 954.9404 49.93237 2954.165 2683.669 1031.328 1696.022 3239.01 1678.839 2265.566 62.5268
median 2327.034 3973.957 7179.067 8149.275 2306.067 7702.689 8249.638 6026.741 4346.291 9486.189 7332.796 4087.044 2799.965
rank 2 4 7 12 1 11 10 8 6 13 9 5 3
C17-F23 mean 2691.435 3077.843 2949.293 3294.999 2826.529 3,,206.505 3089.699 2776.37 2843.433 2903.634 3858.628 2957.034 2950.425
best 2679.378 2941.813 2831.233 3236.012 2780.905 3073.12 3021.808 2743.748 2731.346 2892.146 3741.567 2853.239 2899.501
worst 2704.098 3173.198 3136.276 3380.292 2889.29 3316.166 3188.281 2813.701 2939.296 2918.309 3974.499 3093.225 3010.503
std 10.10131 100.1635 133.6444 62.73727 46.7791 101.8644 72.42882 36.38104 100.4405 11.04206 123.4437 101.7865 45.64687
median 2691.131 3098.181 2914.831 3281.845 2817.96 3218.368 3074.354 2774.014 2851.546 2902.041 3859.223 2940.837 2945.848
rank 1 9 6 12 3 11 10 2 4 5 13 8 7
C17-F24 mean 2896.226 3408.484 3199.101 3463.698 2877.119 3391.269 3316.346 2915.695 2958.944 3090.075 3408.418 3091.683 3257.36
best 2888.001 3305.505 3048.832 3366.821 2870.935 3343.024 3234.967 2877.571 2894.125 3059.462 3368.189 3016.899 3199.87
worst 2902.589 3537.417 3367.271 3632.006 2884.633 3440.512 3459.107 2948.554 3049.884 3125.528 3449.345 3136.157 3339.026
std 6.731113 96.59341 139.9192 122.5211 5.839244 51.92828 98.12749 34.76358 65.36341 29.5475 35.88437 54.9917 59.44844
median 2897.156 3395.506 3190.151 3427.983 2876.453 3390.77 3285.656 2918.328 2945.884 3087.655 3408.07 3106.838 3245.273
rank 2 12 7 13 1 10 9 3 4 5 11 6 8
C17-F25 mean 2912.942 3083.84 2910.493 4702.903 2906.992 3544.987 3087.454 2893.786 2978.111 3041.552 3004.331 2912.146 3085.075
best 2909.21 3059.773 2895.096 4048.889 2890.234 3041.758 3014.644 2883.757 2932.571 2966.697 2991.811 2888.122 3052.956
worst 2917.091 3116.934 2952.85 5574.617 2948.672 4212.467 3186.74 2913.858 3018.136 3093.076 3017.914 2942.563 3105.734
std 3.759012 26.82682 28.25826 635.4398 27.9838 489.9687 74.05925 13.61994 37.24705 55.78418 10.77907 27.8468 23.07507
median 2912.734 3079.325 2897.013 4594.053 2894.53 3462.861 3074.216 2888.764 2980.868 3053.217 3003.8 2908.95 3090.805
rank 5 9 3 13 2 12 11 1 6 8 7 4 10
C17-F26 mean 2893.811 7030.026 7628.776 10,262.03 2900.274 7838.24 8165.049 4768.338 4910.815 5876.503 7785.852 4194.966 4581.948
best 2807.968 5403.73 6234.854 9352.232 2900.076 6226.954 7340.114 4402.959 4478.258 3765.572 6650.013 2819.941 4133.612
worst 2927.204 8050.923 8445.905 11,868.69 2900.493 9673.83 8975.654 5108.717 5422.342 7143.24 8377.255 6371.495 4920.061
std 57.33427 1138.534 973.1733 1181.029 0.207894 1474.61 738.9123 347.4211 482.6334 1477.575 805.9973 1521.981 346.2337
median 2920.037 7332.725 7917.173 9913.604 2900.263 7726.088 8172.214 4780.839 4871.329 6298.6 8058.069 3794.215 4637.06
rank 1 8 9 13 2 11 12 5 6 7 10 3 4
C17-F27 mean 3215.3 3427.03 3367.647 3811.95 3329.272 3609.212 3470.991 3235.764 3266.848 3319.738 5117.272 3295.73 3464.964
best 3201.255 3331.043 3273.591 3507.857 3290.571 3282.225 3306.319 3224.66 3223.755 3262.373 4628.729 3245.382 3436.138
worst 3224.249 3639.124 3449.777 4124.025 3421.134 3869.463 3676.979 3250.099 3311.729 3362.006 5473.508 3341.919 3489.332
std 9.925705 143.5802 92.80698 264.1424 61.78087 259.6228 157.9012 11.04206 38.67463 47.4773 413.4343 40.6175 22.19488
median 3217.847 3368.977 3373.61 3807.959 3302.691 3642.581 3450.333 3234.148 3265.954 3327.287 5183.427 3297.81 3467.192
rank 1 8 7 12 6 11 10 2 3 5 13 4 9
C17-F28 mean 3310.389 3608.074 3279.513 5904.207 3265.216 5091.362 3573.327 3237.176 3491.163 3607.88 3556.346 3350.173 3615.139
best 3210.894 3491.04 3245.999 5568.396 3206.032 4122.444 3506.162 3218.46 3382.682 3493.443 3479.024 3251.203 3506.504
worst 3398.371 3834.864 3314.364 6255.937 3373.749 6052.284 3629.175 3255.912 3763.179 3765.012 3718.62 3531.804 3678.771
std 76.84487 160.5476 27.94958 328.4469 75.21557 889.448 63.20233 20.24324 181.9531 126.2162 109.5052 124.2419 75.08981
median 3316.146 3553.196 3278.844 5896.247 3240.542 5095.36 3578.986 3237.165 3409.395 3586.532 3513.871 3308.842 3637.641
rank 4 10 3 13 2 12 8 1 6 9 7 5 11
C17-F29 mean 3513.911 3928.315 4412.489 5807.492 3672.668 4787.271 5058.604 4072.709 3994.36 4518.153 5204.786 4232.107 4550.496
best 3438.997 3649.853 4031.944 5122.188 3586.227 4310.399 4512.631 4002.885 3773.157 4421.967 4908.07 4047.214 4380.996
worst 3601.815 4058.043 4644.465 6750.722 3787.399 5070.882 5647.867 4125.836 4324.094 4661.445 5483.886 4365.615 4714.488
std 75.06742 187.7454 271.1545 799.9387 87.08749 350.1526 515.2403 54.79906 263.3728 108.3907 309.7752 137.1358 146.445
median 3507.415 4002.683 4486.774 5678.529 3658.523 4883.901 5036.96 4081.058 3940.094 4494.599 5213.594 4257.798 4553.251
rank 1 3 7 13 2 10 11 5 4 8 12 6 9
C17-F30 mean 8305.989 137,769.6 1,529,425 3.03 × 109 9157.746 6.15 × 108 30,762,556 3,049,986 9,525,378 25,150,289 2,426,811 104,576.7 987,308.6
best 6809.307 59,525.81 539,075.8 2.18 × 109 7017.166 7,706,794 5,608,686 1,699,158 1,885,661 19,520,550 2,118,389 8897.047 568,046.1
worst 9524.921 183,375.5 2,708,640 3.35 × 109 10,822.16 1.23 × 109 54,147,488 5,439,819 14,684,335 35,666,572 2,919,985 321,178.6 1,356,063
std 1134.907 56,915.13 907,077.7 5.7 × 108 1704.62 6.99 × 108 19,847,912 1,654,366 6,013,987 7,204,436 345,090 145,516.1 362,444.2
median 8444.864 154,088.4 1,434,992 3.3 × 109 9395.826 6.1 × 108 31,647,026 2,530,484 10,765,759 22,707,017 2,334,435 44,115.67 1,012,563
rank 1 4 6 13 2 12 11 8 9 10 7 3 5
Sum rank 44 183 192 366 57 324 307 122 167 248 245 165 219
Mean rank 1.517241 6.310345 6.62069 12.62069 1.965517 11.17241 10.58621 4.206897 5.758621 8.551724 8.448276 5.689655 7.551724
Total rank 1 6 7 13 2 12 11 3 5 10 9 4 8

Table 4.

Optimization results of the CEC 2017 test suite (for the dimension d=50).

SOA WSO AVOA RSA MPA TSA WOA MVO GWO TLBO GSA PSO GA
C17-F1 mean 151,889.6 2.57 × 1010 9,830,140 9.96 × 1010 5,506,826 5.41 × 1010 7.14 × 109 4,797,753 9.99 × 109 2.21 × 1010 1.82 × 1010 5.74 × 109 8.1 × 109
best 115,387.6 1.88 × 1010 1,170,313 8.71 × 1010 3,290,149 3.98 × 1010 5.01 × 109 3,351,115 5.9 × 109 1.65 × 1010 1.45 × 1010 1.44 × 109 6.57 × 109
worst 247,412.7 3.39 × 1010 26,012,940 1.09 × 1011 8,579,338 6.44 × 1010 1.13 × 1010 5,622,433 1.44 × 1010 3.09 × 1010 2.18 × 1010 1.05 × 1010 9.01 × 109
std 63,842.31 6.64 × 109 11,038,046 9.48 × 109 2,249,133 1.16 × 1010 2.83 × 109 1,007,788 3.47 × 109 6.74 × 109 2.97 × 109 4.87 × 109 1.14 × 109
median 122,379.1 2.51 × 1010 6,068,653 1.01 × 1011 5,078,909 5.6 × 1010 6.13 × 109 5,108,731 9.83 × 109 2.05 × 1010 1.83 × 1010 5.54 × 109 8.41 × 109
rank 1 11 4 13 3 12 6 2 8 10 9 5 7
C17-F3 mean 25,741.16 109,166.7 155,708.8 167,728.7 27,077.85 109,111 239,463.3 55,133.09 121,422.4 98,432.16 189,072.7 227,319.8 289,533.1
best 17,748.75 87,516.26 119,637 152,152.9 18,689.86 93,934.99 149,929.1 35,708.23 109,107.7 82,388.28 170,742.6 169,886.5 206,512.9
worst 31,049.77 131,269.6 189,453.3 182,838.5 32,278.65 143,029.3 381,283.7 88,723.05 137,403.7 10,7613.2 213,623.9 306,999.1 361,157.1
std 5842.384 17,915.62 31,532.21 13,624.19 6102.045 22,781.45 99,541.9 24,999.8 12,061.24 11,298.13 20,728.75 57,433.93 67,162.39
median 27,083.06 108,940.5 156,872.5 167,961.6 28,671.45 99,739.83 213,320.2 48,050.53 119,589.1 101,863.6 185,962.1 216,196.8 295,231.1
rank 1 6 8 9 2 5 12 3 7 4 10 11 13
C17-F4 mean 556.8209 4628.003 711.7594 25,211.16 603.1969 9115.47 1767.649 592.487 1175.328 3505.154 3225.817 978.3787 1594.562
best 537.4312 3095.048 692.7891 16,625.85 544.7605 7469.591 1392.045 533.3314 951.1455 2035.156 2692.306 831.7601 1584.14
worst 600.4123 6512.632 744.1292 30,113.72 642.9742 11,041.53 2186.232 633.6151 1702.492 5193.195 3440.077 1063.683 1605.234
std 29.38858 1751.262 22.72217 6158.629 43.34086 1468.831 333.7792 48.89051 353.3024 1632.081 357.6048 103.4355 10.48297
median 544.72 4452.167 705.0597 27,052.53 612.5264 8975.38 1746.16 601.5007 1023.838 3396.133 3385.444 1009.036 1594.437
rank 1 11 4 13 3 12 8 2 6 10 9 5 7
C17-F5 mean 677.7792 825.0179 879.2559 1166.95 721.1215 1151.616 1032.234 716.9972 732.7364 1062.166 824.3543 843.4191 930.9574
best 656.4368 798.6558 847.0349 1146.761 700.2873 1006.991 966.5428 655.0431 654.3651 1050.273 768.6373 757.5923 874.5555
worst 704.4044 854.3394 923.0372 1180.923 741.884 1243.544 1058.35 768.2161 842.6329 1085.351 863.1571 935.7099 986.5072
std 23.359 23.67232 32.825 15.67259 16.98195 101.2598 43.90967 46.69174 80.43853 15.84562 44.50277 73.25487 46.17203
median 675.1377 823.5383 873.4757 1170.059 721.1573 1177.965 1052.021 722.3649 716.9737 1056.52 832.8113 840.1871 931.3835
rank 1 6 8 13 3 12 10 2 4 11 5 7 9
C17-F6 mean 612.5444 650.0934 663.6411 702.8348 636.3891 697.6476 697.9072 641.0802 624.8983 664.2849 661.2626 651.6176 648.1166
best 608.3547 647.0002 658.5488 700.4264 610.8922 689.7925 695.4772 627.1604 621.0722 655.5853 656.0718 644.4713 637.0315
worst 618.0937 652.6056 669.415 705.9343 658.9156 705.5216 701.5624 662.1438 634.2509 670.3405 664.3465 656.3579 653.6417
std 4.065504 2.809484 5.020008 2.578301 21.6058 6.447668 2.764061 15.49878 6.284174 6.536734 3.64112 5.419492 7.510199
median 611.8646 650.3839 663.3002 702.4892 637.8744 697.6381 697.2946 637.5083 622.1351 665.6069 662.3161 652.8207 650.8966
rank 1 6 9 13 3 11 12 4 2 10 8 7 5
C17-F7 mean 1020.053 1634.936 1719.618 1959.322 1061.083 1830.724 1790.789 1104.083 1082.367 1452.483 1449.5 1226.391 1392.31
best 984.9752 1274.275 1644.257 1873.413 1012.389 1488.422 1657.407 1042.23 977.2225 1415.913 1271.118 1090.999 1331.588
worst 1069.875 1936.749 1789.939 2069.047 1096.42 2051.525 1928.988 1216.458 1156.252 1470.253 1586.373 1346.737 1447.051
std 36.24558 272.8645 61.93246 83.88886 35.62031 252.3578 135.164 77.13688 75.41492 24.69756 142.0339 110.3465 48.90072
median 1012.68 1664.36 1722.138 1947.414 1067.762 1891.475 1788.38 1078.822 1097.996 1461.884 1470.255 1233.914 1395.3
rank 1 9 10 13 2 12 11 4 3 8 7 5 6
C17-F8 mean 992.8944 1119.935 1143.249 1485.684 1054.1 1501.057 1300.005 1093.326 1037.12 1343.492 1160.173 1090.87 1239.259
best 958.4409 1089.39 1094.35 1452.256 984.2098 1375.148 1199.351 1031.358 993.6126 1294.575 1151.218 1064.359 1164.301
worst 1018.161 1182.289 1193.203 1509.275 1144.524 1561.062 1386.4 1211.078 1054.829 1379.624 1175.097 1135.192 1276.922
std 25.38413 43.54379 56.20376 23.96556 67.8529 87.41298 78.03448 81.14765 29.12162 38.09022 10.62307 31.92935 53.04527
median 997.4879 1104.031 1142.721 1490.603 1043.832 1534.009 1307.133 1065.433 1050.02 1349.885 1157.188 1081.965 1257.907
rank 1 6 7 12 3 13 10 5 2 11 8 4 9
C17-F9 mean 3379.968 31,574.54 13,994.58 38,384.66 3535.572 43,997.3 38,999.55 12,924.53 10,955.82 24,490.33 11,230.46 13,220.99 11,936.19
best 2720.798 27,546.88 13,334.96 36,059.86 2795.909 34,228.79 27,771.85 4379.022 7695.713 17,011.15 10,226.78 8972.343 9776.976
worst 4482.205 35,368.01 14,911.51 40,280.9 4766.806 51,238.8 57,115.19 20,429.49 13,132.49 27,535.96 12,132.64 21,544.05 14,035.6
std 766.3366 4276.902 681.8704 1998.844 858.076 7407.689 12,869.39 8072.639 2466.082 5024.465 792.2221 5669.612 2264.86
median 3158.435 31,691.64 13,865.93 38,598.94 3289.786 45,260.8 35,555.58 13,444.81 11,497.54 26,707.11 11,281.22 11,183.79 11,966.1
rank 1 10 8 11 2 13 12 6 3 9 4 7 5
C17-F10 mean 6174.072 7403.704 8579.601 14,818.96 6667.021 13,370.03 12,530.29 7041.612 7036.968 14,639.16 8868.741 8635.025 11,353.66
best 5757.895 6703.828 8018.602 14,572.31 5919.308 12,643.44 11,659.82 6312.651 6849.65 13,468.42 7973.388 7336.097 10,137.65
worst 6627.51 7941.478 9205.324 15,177.46 7192.289 13,961.87 13,907.52 7530.854 7297.502 15,497.98 9980.347 9821.611 11,876.02
std 461.6323 515.452 503.2166 286.0404 585.7901 662.7266 1020.996 557.1729 220.1985 848.7871 837.357 1033.431 825.7338
median 6155.442 7484.756 8547.239 14,763.03 6778.245 13,437.41 12,276.92 7161.472 7000.36 14,795.11 8760.614 8691.196 11,700.49
rank 1 5 6 13 2 11 10 4 3 12 8 7 9
C17-F11 mean 1334.96 4491.299 1635.402 22,214.14 1309.933 10,609.27 3565.628 1464.313 8372.954 5000.771 15,005.37 1892.931 15,726.03
best 1281.171 3159.729 1507.538 19,751.85 1305.562 6841.722 3031.132 1362.16 4716.472 4243.983 14,069.52 1462.895 11,246.91
worst 1372.22 6882.562 1798.581 24,081.65 1315.877 15,049.35 3780.766 1592.317 12,480.16 5708.219 17,016.79 2863.255 19,576.5
std 38.83575 1664.8 134.2452 1809.233 4.400385 4211.171 358.468 112.5475 3546.225 655.6899 1355.471 655.2459 3430.853
median 1343.224 3961.453 1617.745 22,511.53 1309.145 10,273 3725.307 1451.387 8147.593 5025.441 14,467.58 1622.787 16,040.36
rank 2 7 4 13 1 10 6 3 9 8 11 5 12
C17-F12 mean 11,251,731 5.27 × 109 78,049,621 7.57 × 1010 12,693,027 1.72 × 1010 1.61 × 109 98,207,747 1.57 × 109 3.95 × 109 2.31 × 109 1.16 × 109 2.07 × 108
best 10,038,799 1.65 × 109 33,060,130 5.52 × 1010 9,956,212 7.73 × 109 8.92 × 108 63,359,996 3.8 × 108 2.82 × 109 7.6 × 108 2.74 × 108 96,807,585
worst 12,129,544 9.38 × 109 1.21 × 108 1.04 × 1011 18,145,198 2.85 × 1010 2.96 × 109 1.62 × 108 2.93 × 109 5.13 × 109 4.15 × 109 1.74 × 109 3.39 × 108
std 1,025,491 3.48 × 109 46,894,592 2.24 × 1010 3,729,890 8.96 × 109 9.5 × 108 46,032,952 1.37 × 109 9.8 × 108 1.4 × 109 6.93 × 108 1.02 × 108
median 11,419,290 5.02 × 109 79,267,889 7.19 × 1010 11,335,349 1.62 × 1010 1.3 × 109 83,612,325 1.48 × 109 3.93 × 109 2.16 × 109 1.32 × 109 1.95 × 108
rank 1 11 3 13 2 12 8 4 7 10 9 6 5
C17-F13 mean 25,194.61 7.45 × 108 158,443 4.58 × 1010 29,207.77 1.23 × 1010 1.55 × 108 169,862.1 2.14 × 108 6.76 × 108 19,712,046 2.11 × 108 26,307,383
best 14,947.67 39,849,034 36,363.7 2.32 × 1010 14,829.62 5.77 × 109 72,249,484 89,730.53 1.19 × 108 4.77 × 108 33,125.95 60217.58 6,804,282
worst 35,197.79 2.32 × 109 349,245.4 6.59 × 1010 49,867.22 1.62 × 1010 2.35 × 108 250,596.3 3.63 × 108 7.89 × 108 66,446,165 5.9 × 108 43,575,192
std 10,557.9 1.08 × 109 133,793.4 1.79 × 1010 16,453.73 4.55 × 109 67,992,278 65,749.65 1.14 × 108 1.41 × 108 31,690,714 2.77 × 108 15,084,746
median 25,316.49 3.12 × 108 124,081.5 4.71 × 1010 26,067.12 1.36 × 1010 1.56 × 108 169,560.9 1.88 × 108 7.19 × 108 6184,447 1.28 × 108 27,425,029
rank 1 11 3 13 2 12 7 4 9 10 5 8 6
C17-F14 mean 1561.629 954,429.1 1301,714 51,521,240 1644.844 11,042,571 6537,253 338,362 2,186,341 1,214,913 16,125,876 177,015.6 11,328,374
best 1551.57 40,522.92 403,134.7 15,801,584 1610.492 744,015.3 1234,192 193,899.1 117,686.7 1,015,556 3,656,077 54,705.12 8,041,233
worst 1569.011 2,245,963 3,100,586 1.04 × 108 1665.859 38,689,467 18,106,774 480,695.4 4,353,688 1,446,289 26,477,284 410,064.8 15,650,354
std 7.48164 929,949.3 1226,148 37,650,671 24.55157 18,475,034 7,877,558 121,825.3 2,228,784 193,566.3 10,346,083 15,8781.1 3165,277
median 1562.968 765,615.1 851,568.7 42,984,409 1651.514 2,368,402 3,404,022 339,426.6 2,136,996 1,198,904 17,185,072 121,646.3 10,810,955
rank 1 5 7 13 2 10 9 4 8 6 12 3 11
C17-F15 mean 2088.202 84,644.13 40,352.97 4.46 × 109 2168.064 2.15 × 109 45,457,765 106,616 23,648,137 50,130,625 2.1 × 108 20,135.54 13,007,299
best 2001.116 19,632.75 24,871.69 3.48 × 109 2081.998 7332003 12,695,487 61,228.51 114,896.2 24,391,486 20291.99 2938.625 1,429,335
worst 2202.268 176,250.9 74,394 5.28 × 109 2262.088 6.23 × 109 86,925,294 163,102.2 42,481,430 77,779,135 8.16 × 108 40,169.41 25,370,774
std 84.61488 66,115.44 22,955.17 7.97 × 108 77.26539 2.81 × 109 35,216,059 42,226.99 18,140,241 25,125,637 4.04 × 108 17,100.37 9,825,680
median 2074.712 71,346.42 31,073.09 4.53 × 109 2164.086 1.19 × 109 41,105,139 101,066.6 25,998,110 49,175,940 12,713,833 18,717.06 12,614,543
rank 1 5 4 13 2 12 9 6 8 10 11 3 7
C17-F16 mean 2737.231 3413.809 4503.424 7943.425 2910.262 5681.85 6366.838 3202.22 3082.343 5298.307 4079.109 3392.654 3966.724
best 2549.162 2716.472 4180.052 5899.312 2532.098 4684.45 5729.784 2828.437 2728.369 5156.685 3701.751 2883.776 3447.318
worst 2910.818 3865.438 4935.667 11,948.51 3329.982 6106.082 6736.105 3693.078 3311.269 5434.487 4494.833 3690.971 4613.582
std 148.0198 530.6386 363.5425 2755.255 326.6354 668.1979 465.9646 390.8859 248.6798 114.3378 375.0628 374.9784 542.6677
median 2744.471 3536.663 4448.988 6962.941 2889.485 5968.433 6500.731 3143.683 3144.867 5301.028 4059.925 3497.935 3902.998
rank 1 6 9 13 2 11 12 4 3 10 8 5 7
C17-F17 mean 2573.195 3002.378 3658.258 11,639.65 2700.396 5430.256 4790.562 3274.99 2870.234 3934.082 3937.182 3256.484 3396.164
best 2411.363 2677.716 3193.284 8466.86 2459.043 3655.951 3430.344 2935.277 2516.354 3671.376 3461.219 3075.895 3257.524
worst 2687.187 3690.493 4212.583 15,174.64 2833.242 7076.82 5593.094 3534.417 3082.95 4167.482 4255.079 3551.107 3543.127
std 115.9525 464.2714 492.9618 2763.849 165.2191 1442.127 967.311 265.5602 264.1476 206.5056 348.598 224.8963 117.1755
median 2597.115 2820.652 3613.583 11,458.55 2754.65 5494.126 5069.405 3315.133 2940.815 3948.735 4016.215 3199.467 3392.002
rank 1 4 8 13 2 12 11 6 3 9 10 5 7
C17-F18 mean 14,578.01 2,805,300 2,568,723 1.2 × 108 15,143.98 45,107,782 61,393,853 2,423,534 21,017,655 8731,271 8,959,584 832,165.9 16,730,316
best 4589.064 379,650.7 332,655.2 53,792,821 4782.991 5,112,949 12,472,675 1,316,487 3,654,688 2,959,680 4,236,144 500,424.3 7,543,771
worst 30,709.1 5,279,270 4,705,067 1.66 × 108 32,192.73 1.12 × 108 1.43 × 108 3,480,084 64,837,312 21,724,952 16,743,556 1,208,421 21,978,246
std 11,718.82 2,146,247 2,215,520 55,161,299 12,301.32 47,374,611 61,960,905 1,015,362 29,414,178 8,763,297 5,701,618 292,071.8 6,671,844
median 11,506.93 2,781,141 2,618,585 1.29 × 108 11,800.09 31,796,854 44,854,458 2,448,782 7,789,311 5,120,226 7,429,317 809,909.1 18,699,624
rank 1 6 5 13 2 11 12 4 10 7 8 3 9
C17-F19 mean 2108.057 159,032.8 276,582.5 4.09 × 109 2212.473 1.16 × 109 3,880,347 5,795,751 11,522,364 69,314,944 481,438.7 27,395.04 852,195.6
best 2041.296 36,866.49 96,991.5 2.76 × 109 2118.389 10389370 424,737.4 1,799,228 2,465,418 29,753,913 276,793.4 6758.912 657,534.7
worst 2184.699 419,582.6 570,566.3 5.06 × 109 2328.246 2.36 × 109 7,483,304 9,042,447 32,549,618 1.43 × 108 1,055,175 78,011.97 1,075,172
std 77.04148 178,299 205,522.6 1.02 × 109 108.4181 1.32 × 109 3,181,528 3,059,230 14,306,749 52,264,278 382,629.3 33,896.96 171,296
median 2103.117 89,841.03 219,386.1 4.27 × 109 2201.628 1.14 × 109 3,806,673 6,170,664 5,537,210 52,379,219 296,893.2 12,404.65 838,037.7
rank 1 4 5 13 2 12 8 9 10 11 6 3 7
C17-F20 mean 2547.209 3273.289 3337.748 4223.731 2931.538 3847.953 4145.357 3157.849 3220.128 3846.377 4165.34 3170.407 3108.672
best 2498.065 2844.233 2688.235 3927.478 2786.566 3412.071 3572.722 2814.451 2952.323 3618.013 3846.16 2963.648 3017.065
worst 2648.126 3919.758 3912.457 4391.213 3205.982 4148.526 4368.731 3500.378 3597.963 4078.028 4468.586 3305.249 3201.274
std 68.60929 507.0025 524.2096 204.2398 187.4237 312.5293 382.4528 282.9635 276.6289 252.1705 255.2723 155.2787 92.03002
median 2521.322 3164.582 3375.15 4288.117 2866.802 3915.608 4319.989 3158.283 3165.113 3844.734 4173.307 3206.364 3108.174
rank 1 7 8 13 2 10 11 4 6 9 12 5 3
C17-F21 mean 2461.015 2750.03 2785.955 3080.695 2442.558 2978.155 3074.598 2538.401 2541.013 2858.889 2878.604 2691.435 2775.299
best 2454.062 2655.45 2655.912 2968.624 2438.788 2961.782 2916.837 2465.581 2500.98 2816.416 2802.947 2602.644 2699.723
worst 2467.75 2890.739 2985.839 3173.847 2445.937 3018.498 3252.448 2618.492 2568.759 2900.466 2921.082 2738.388 2838.696
std 5.753449 100.6273 142.2127 97.29591 3.785764 26.98508 139.2031 75.69416 28.66691 35.38466 53.10801 60.48597 63.22481
median 2461.123 2726.966 2751.035 3090.154 2442.753 2966.17 3064.553 2534.767 2547.157 2859.337 2895.194 2712.354 2781.388
rank 2 6 8 13 1 11 12 3 4 9 10 5 7
C17-F22 mean 5068.179 10,601.63 11,695.73 17,156.72 5289.649 14,744.41 14,773.48 9918.28 8391.527 16,328.37 12,006.95 11,379.86 11,852.76
best 2317.659 9792.013 9254.48 16,976.74 2386.837 13,539.03 12,269.29 9328.101 6397.783 15,366.03 11,736.64 9262.03 5080.869
worst 8010.131 11,189.41 13,600.29 17,419.31 8618.209 15,424.94 16,718.84 10,360.01 10,211.59 17,081.38 12,207.05 13,321.13 15,030.32
std 3175.556 587.4619 1976.242 202.7537 3338.394 827.801 1899.776 440.2749 1597.655 721.302 208.2034 1660.84 4566.475
median 4972.464 10,712.55 11,964.08 17,115.42 5076.776 15,006.83 15052.9 9992.504 8478.367 16,433.04 12,042.05 11,468.14 13,649.93
rank 1 5 7 13 2 10 11 4 3 12 9 6 8
C17-F23 mean 2879.864 3742.803 3333.282 3984.37 3013.484 4203.96 3625.626 2987.978 3030.149 3353.519 4909.23 3393.538 3411.219
best 2819.095 3528.564 3242.024 3931.858 2911.823 3785.87 3524.337 2952.645 2998.021 3281.372 4698.938 3325.579 3287.366
worst 2929.666 3941.54 3420.534 4030.28 3057.88 4675.038 3725.834 3017.048 3058.198 3472.351 5093.602 3455.819 3511.652
std 45.73851 215.66 84.27723 41.04961 68.2742 415.8831 87.17086 27.56366 26.83748 82.51679 161.8938 53.58173 114.0835
median 2885.347 3750.553 3335.286 3987.67 3042.116 4177.466 3626.167 2991.11 3032.189 3330.177 4922.189 3396.376 3422.929
rank 1 10 5 11 3 12 9 2 4 6 13 7 8
C17-F24 mean 3083.504 4142.676 3560.758 4611.799 3081.981 4037.358 3901.95 3096.846 3208.072 3525.045 4499.5 3660.766 3832.45
best 3015.965 3876.67 3440.367 4085.627 3000.511 3762.786 3823.238 3056.288 3106.145 3473.443 4461.401 3604.282 3679.231
worst 3132.978 4662.206 3761.438 5903.316 3136.003 4367.077 3988.185 3126.944 3377.68 3567.211 4558.036 3744.37 4008.357
std 51.40778 355.0229 139.0862 869.707 58.68838 279.9751 68.7295 29.97032 117.5406 46.10856 44.92477 64.59743 155.6822
median 3092.536 4015.914 3520.614 4229.127 3095.705 4009.785 3898.188 3102.076 3174.232 3529.763 4489.28 3647.206 3821.106
rank 2 11 6 13 1 10 9 3 4 5 12 7 8
C17-F25 mean 3068.733 4544.506 3193.318 12,627.24 3087.808 6295.735 4867.662 3090.15 3831.696 4514.777 4376.108 3145.639 4421.074
best 3046.855 3802.561 3163.265 10,093.24 3054.996 5817.769 4493.166 3057.295 3605.51 3911.35 4001.137 3096.16 4179.04
worst 3077.521 5346.191 3243.541 14,183.95 3131.849 6738.606 5247.977 3113.089 4055.253 4952.488 5087.889 3185.549 4659.918
std 14.64504 632.2521 34.79092 1922.174 33.4426 392.6728 344.0079 23.71 233.4356 519.0428 511.0707 39.00329 196.3794
median 3075.279 4514.635 3183.232 13,115.89 3082.194 6313.284 4864.752 3095.108 3833.011 4597.634 4207.703 3150.422 4422.67
rank 1 10 5 13 2 12 11 3 6 9 7 4 8
C17-F26 mean 4455.594 10,887.89 11,546.28 15,965.14 4869.194 14,453.46 15,596.31 6182.373 7275.879 9760.462 12,162.55 7406.202 7234.428
best 3501.58 6702.71 10,993.2 15,295.97 3470.604 13,342.37 14,726.99 5832.205 6155.413 9467.029 11,786.48 3655.993 6898.45
worst 6191.431 13,062.05 12,099.17 16,992.01 6448.084 15,734.17 16,328.64 6713.88 8916.753 10,118.65 12,597.7 9175.091 7781.243
std 1226.994 2918.176 452.4794 735.8058 1422.756 985.4345 658.776 386.3427 1291.61 270.3168 338.5611 2584.358 392.6468
median 4064.682 11,893.4 11,546.38 15,786.29 4779.045 14,368.66 15,664.8 6091.705 7015.674 9728.086 12,133.01 8396.863 7129.01
rank 1 8 9 13 2 11 12 3 5 7 10 6 4
C17-F27 mean 3363.189 4366.514 3897.689 5125.112 3448.795 5237.028 4903.756 3470.777 3717.304 3693.737 8470.607 3854.516 4433.001
best 3320.606 4286.133 3848.523 4720.746 3366.621 4761.12 4426.306 3432.261 3636.637 3635.281 8197.85 3698.911 4182.635
worst 3430.944 4491.872 3970.348 5408.718 3607.609 5915.32 5499.852 3571.634 3830.143 3756.612 8860.917 4102.243 4668.505
std 49.36455 94.88507 54.71087 330.3539 110.5841 485.8052 449.642 67.53284 87.25992 55.50564 322.7935 173.0623 198.6077
median 3350.604 4344.025 3885.944 5185.491 3410.475 5135.835 4844.433 3439.606 3701.218 3691.528 8411.831 3808.456 4440.433
rank 1 8 7 11 2 12 10 3 5 4 13 6 9
C17-F28 mean 3304.026 5927.069 3619.749 11,797.14 3373.545 6674.615 5136.264 3310.385 4426.418 5582.872 5201.752 3869.901 4966.713
best 3279.151 5470.669 3530.722 10,414.72 3341.683 5799.475 4614.257 3301.588 4091.054 4696.446 5136.095 3456.669 4889.397
worst 3330.152 6322.616 3716.895 15,468.78 3429.377 8088.887 5807.894 3314.652 4863.695 6048.066 5331.294 4264.888 5054.661
std 21.30892 374.6972 91.86549 2452.27 38.51731 1032.791 510.3959 6.127407 361.6129 603.6288 88.70492 382.4002 75.04482
median 3303.4 5957.496 3615.689 10,652.52 3361.561 6405.05 5061.453 3312.649 4375.462 5793.489 5169.809 3879.023 4961.397
rank 1 11 4 13 3 12 8 2 6 10 9 5 7
C17-F29 mean 4311.503 5508.011 5680.663 20,771.09 4536.4 8098.192 8442.254 5166.941 4755.15 6354.818 8566.63 5084.367 6583.69
best 4038.342 4914.424 5522.082 10,858.34 4288.411 6715.261 6101.824 4992.053 4634.581 6001.988 7009.127 4698.529 6508.721
worst 4509.912 6458.317 5834.624 33,002.78 4775.32 10,262.49 10,228.64 5303.74 4937.432 6842.113 11,314.84 5645.839 6630.906
std 198.4451 720.6455 127.7043 9862.853 200.54 1638.244 1783.724 129.1374 137.3209 361.7188 1938.806 463.4686 52.64746
median 4348.878 5329.651 5682.974 19,611.63 4540.934 7707.507 8719.274 5185.984 4724.293 6287.585 7971.274 4996.55 6597.567
rank 1 6 7 13 2 10 11 5 3 8 12 4 9
C17-F30 mean 2,025,569 35,167,304 23,274,855 5.86 × 109 2,682,820 1.04 × 109 2.59 × 108 80,472,757 1.24 × 108 2.86 × 108 1.97 × 108 5990,562 58,956,549
best 1,181,088 23,290,188 14,200,523 3.6 × 109 1,328,294 1.77 × 108 98,570,183 51,907,046 73641400 1.95 × 108 1.51 × 108 1211,278 45,838,053
worst 2,875,328 42,761,447 31,913,446 9.19 × 109 3,372,211 2.89 × 109 4.62 × 108 1.34 × 108 1.7 × 108 5.03 × 108 2.58 × 108 18,526,499 66,979,535
std 698,314.3 8,325,550 8701,063 2.41 × 109 918,657.5 1.26 × 109 1.52 × 108 37,734,532 41,204,160 1.47 × 108 449,807,88 8,368,296 9,118,859
median 2,022,930 37,308,790 23,492,726 5.32 × 109 3,015,388 5.51 × 108 2.37 × 108 68,043,751 1.27 × 108 2.22 × 108 1.89 × 108 2,112,235 61,504,304
rank 1 5 4 13 2 12 10 7 8 11 9 3 6
Sum rank 32 216 182 366 62 325 287 115 159 256 264 157 218
Mean rank 1.103448 7.448276 6.275862 12.62069 2.137931 11.2069 9.896552 3.965517 5.482759 8.827586 9.103448 5.413793 7.517241
Total rank 1 7 6 13 2 12 11 3 5 9 10 4 8

Table 5.

Optimization results of the CEC 2017 test suite (for the dimension d=100).

SOA WSO AVOA RSA MPA TSA WOA MVO GWO TLBO GSA PSO GA
C17-F1 mean 160,265.1 1.19 × 1011 4.08 × 109 2.48 × 1011 5 × 108 1.31 × 1011 6.53 × 1010 67,475,871 5.52 × 1010 9.46 × 1010 1.4 × 1011 2.14 × 1010 6.99 × 1010
best 138,023.5 1.11 × 1011 1.98 × 109 2.44 × 1011 3.71 × 108 1.18 × 1011 6.11 × 1010 57,348,883 3.89 × 1010 7.98 × 1010 1.18 × 1011 1.65 × 1010 6.09 × 1010
worst 207,953.1 1.25 × 1011 5.86 × 109 2.5 × 1011 7.33 × 108 1.47 × 1011 6.77 × 1010 77,330,536 6.37 × 1010 1.12 × 1011 1.58 × 1011 2.72 × 1010 7.63 × 1010
std 32,666.58 5.84 × 109 1.59 × 109 2.86 × 109 1.6 × 108 1.44 × 1010 2.97 × 109 10,406,022 1.16 × 1010 1.35 × 1010 1.71 × 1010 4.42 × 109 6.58 × 109
median 147,541.9 1.2 × 1011 4.23 × 109 2.49 × 1011 4.47 × 108 1.3 × 1011 6.61 × 1010 67,612,033 5.91 × 1010 9.31 × 1010 1.42 × 1011 2.1 × 1010 7.13 × 1010
rank 1 10 4 13 3 11 7 2 6 9 12 5 8
C17-F3 mean 155,460.5 284,175.9 347,477.9 343,395.2 163,200.2 375,331.1 977,486.3 500,947.0 389,167.5 329,791.4 365,707.5 607,827.5 654,898.7
best 136,109.2 248,717.4 339,354.5 331,243.9 142,444.6 312,194.3 943,418.6 444,428.5 374,416.5 301,764.9 354,759.5 419,980.8 516,193.8
worst 164,612.9 309,081.9 355,262.9 350,541.3 173,294.4 415,302.3 1,042,632.0 632,522.5 415,170.4 355,744.3 377,857.9 772,544 754,873.2
std 13,110.98 28,313.85 6723.431 9036.029 14,518.07 44,174.85 46,210.51 88,310.45 17,980.22 29,865.05 9617.273 14,9726.7 116,056.6
median 160,559.9 289,452.2 347,647.2 345,897.8 168,530.8 386,913.8 961,947.5 463,418.4 383,541.7 330,828.1 365,106.3 619,392.6 674,264
rank 1 3 6 5 2 8 13 10 9 4 7 11 12
C17-F4 mean 707.8421 19,140.58 1615.548 79,883.06 1078.93 19,621.12 13,056.76 745.6667 5449.769 9178.908 36,332.13 3066.08 9469.057
best 655.7759 14,643.47 1348.811 72,405.03 1013.777 14,895.87 10,390.22 702.4754 3735.491 6841.936 25,952.88 2030.326 9196.622
worst 793.6724 21,181.19 1785.136 89,013.13 1187.742 28,200.33 14,,767.67 773.1848 7492.231 10,520.72 45,851.15 4909.819 9906.689
std 60.21498 3087.898 197.5832 6886.744 75.37681 6081.237 1906.107 31.28424 1791.353 1681.483 8202.682 1313.62 306.1485
median 690.96 20,368.84 1664.122 79,057.04 1057.1 17,694.15 13,534.58 753.5032 5285.676 9676.486 36,762.24 2662.088 9386.458
rank 1 10 4 13 3 11 9 2 6 7 12 5 8
C17-F5 mean 1140.386 1416.959 1337.534 2014.712 1240.094 2115.385 1999.848 1237.633 1155.592 1860.505 1347.479 1399.646 1716.961
best 1078.186 1389.332 1325.12 1977.422 1195.626 2036.245 1909.846 1113.65 1084.952 1792.429 1271.784 1348.014 1657.313
worst 1174.568 1466.582 1347.384 2051.417 1308.247 2283.080 2096.681 1333.125 1222.116 1994.053 1469.717 1467.549 1744.248
std 42.78946 34.79746 9.317251 37.35075 49.91629 113 76.57659 97.18324 56.28314 90.68752 86.24644 53.25039 40.1947
median 1154.395 1405.962 1338.816 2015.004 1228.252 2071.107 1996.433 1251.878 1157.651 1827.769 1324.208 1391.51 1733.142
rank 1 8 5 12 4 13 11 3 2 10 6 7 9
C17-F6 mean 640.8564 671.2647 664.0195 708.4028 635.4878 720.0932 702.7487 677.6025 641.7199 687.1312 668.1679 665.195 667.7512
best 638.4984 665.4193 659.8006 703.2776 632.7878 708.063 692.7168 661.6266 636.6993 680.3454 666.4344 661.4675 662.3638
worst 645.8414 687.6795 668.4418 711.4416 640.1923 730.9568 716.0015 693.8966 645.3746 696.9215 669.6235 670.454 674.3769
std 3.412407 10.94671 3.561852 3.608402 3.400557 10.07273 10.16945 13.63377 3.924944 7.304814 1.69535 4.126496 5.003959
median 639.5429 665.98 663.9178 709.446 634.4854 720.6764 701.1382 677.4434 642.4029 685.629 668.3068 664.4292 667.132
rank 2 8 4 12 1 13 11 9 3 10 7 5 6
C17-F7 mean 1893.552 3374.351 3157.709 3828.487 2006.673 3664.688 3488.485 2248.066 2145.731 2970.465 2998.831 2589.66 2744.412
best 1757.932 3209.741 2991.056 3733.397 1831.281 3130.538 3237.059 2030.148 2005.574 2855.161 2786.07 2157.752 2606.048
worst 2019.125 3753.746 3297.533 3909.372 2119.133 4341.917 3644.585 2476.499 2342.976 3102.649 3161.247 2829.485 2825.746
std 114.7911 257.1896 153.159 75.52237 124.2497 501.5494 182.1772 189.4768 147.1537 121.8524 178.6652 315.2845 100.1396
median 1898.576 3266.959 3171.124 3835.589 2038.139 3593.148 3536.148 2242.807 2117.187 2962.026 3024.004 2685.703 2772.926
rank 1 10 9 13 2 12 11 4 3 7 8 5 6
C17-F8 mean 1431.669 1802.604 1766.254 2528.82 1483.671 2517.501 2210.127 1482.502 1540.977 2240.139 1883.447 1919.521 2069.916
best 1288.825 1707.765 1707.542 2502.557 1317.806 2416.13 2128.762 1356.216 1467.944 2124.134 1857.322 1747.085 2014.745
worst 1505.145 1846.735 1795.721 2544.961 1637.492 2615.076 2313.552 1578.711 1603.175 2340.597 1932.538 2074.104 2101.56
std 97.56967 63.86616 40.49818 18.33389 131.5389 83.6966 79.91965 97.93548 56.07926 95.53038 35.38708 164.7306 39.18582
median 1466.353 1827.959 1780.877 2533.881 1489.693 2519.399 2199.096 1497.541 1546.395 2247.912 1871.965 1928.448 2081.68
rank 1 6 5 13 3 12 10 2 4 11 7 8 9
C17-F9 mean 19,364.46 82,669.58 27,172.11 79,373.17 22,818.43 137,756.3 59,269.65 68,461.86 45,236.99 69,329.59 26,731.7 30,740.75 48,051.43
best 16,807.53 75,191.45 22,605.98 76,723.33 17,418.05 108,475.1 45,027.85 49,383.76 33,072.81 65,899.36 24,236.3 25,972.61 45,151.63
worst 21,107.66 91,644.35 30,594.59 81,543.18 25,883.72 152,399.4 83,531.69 94,754.6 54,921.68 73,999.44 30,955.57 36,306.87 53,358.57
std 2103.88 7174.092 3328.994 2100.287 3868.815 19,968.74 17,085.29 19,622.14 9095.293 3435.528 2919.456 5374.775 3799.396
median 19,771.33 81,921.27 27,743.93 79,613.09 23,985.98 145,075.3 54,259.52 64,854.53 46,476.73 68,709.78 25,867.47 30,341.75 46,847.75
rank 1 12 4 11 2 13 8 9 6 10 3 5 7
C17-F10 mean 12,718.41 25,000.53 16,130.00 32,371.07 14,957.25 29,288.9 27,809.40 16,429.39 20,918.75 32,258.28 16,555.1 17,941.46 26,975.78
best 12,215.97 17,070.00 13,311.48 31,423.28 13,758.01 28,082.1 25,632.71 12,929.29 16,553.94 31,909.45 15,209.4 16,127.12 26,382.45
worst 13,595.73 31,663.57 18,484.04 32,801.76 15,544.55 30,431.1 29,064.27 20,010.88 32,186.21 32,592.30 17,295.4 20,010.14 27,903.87
std 603.51 7406.58 2244.45 647.84 825.34 969.3 1538.77 2909.97 7526.20 360.10 923.7 1735.06 702.90
median 12,530.97 25,634.28 16,362.23 32,629.62 15,263.23 29,321.1 28,270.31 16,388.69 17,467.43 32,265.69 16,857.76 17,814.29 26,808.41
rank 1 8 3 13 2 11 10 4 7 12 5 6 9
C17-F11 mean 2576.639 66,539.98 66,864.48 215,441.7 4466.554 74,278.42 233,670.5 5121.713 73,277.27 54,827.31 182,410.7 80,069.76 163,604.5
best 2351.245 48,807.46 60,071.57 164,806.4 3731.435 57,060.97 147,832.1 4503.97 59,898.28 49,308.24 150,790.3 50,850.22 122,067.2
worst 2838.85 92,451.67 79,917.87 307,014.4 5502.63 83,711.11 404,045.3 6212.619 87,020.96 63,160.31 215,076.3 97,950.76 207,411.1
std 224.0385 19,508.04 9184.966 64,071.68 763.2635 11,773.96 115,695.8 775.776 11,363.38 5914.53 27,214.48 22,176.82 41,642.89
median 2558.232 62450.4 63,734.24 194,972.9 4316.076 78,170.81 191,402.3 4885.131 73,094.91 53,420.35 181,888.2 85,739.03 162,469.8
rank 1 5 6 12 2 8 13 3 7 4 11 9 10
C17-F12 mean 21,615,544 5.33 × 1010 6.87 × 108 1.79 × 1011 2.66 × 108 6.03 × 1010 1.25 × 1010 5.51 × 108 1.78 × 1010 2.51 × 1010 6.17 × 1010 7.41 × 109 1.34 × 1010
best 10,630,715 4.58 × 1010 3.65 ×108 1.34 × 1011 1.03 × 108 4.46 × 1010 9.28 × 109 2.54 × 108 1.19 × 1010 1.69 × 1010 4.86 × 1010 2.54 × 109 1.17 × 1010
worst 32,253,244 6.1 × 1010 1.1 × 109 2.08 × 1011 3.55 × 108 8.39 × 1010 1.46 × 1010 9.23 × 108 3.18 × 1010 3.8 × 1010 6.66 × 1010 1.75 × 1010 1.58 × 1010
std 9525,992 6.22 × 109 3.16 × 108 3.4 × 1010 1.13 × 108 1.72 × 1010 2.28 × 109 2.95 × 108 9.38 × 109 9.05 × 109 8.78 × 109 6.81 × 109 2.01 × 109
median 21,789,109 5.33 × 1010 6.44 × 108 1.87 × 1011 3.04 × 108 5.64 × 1010 1.31 × 1010 5.13 × 108 1.38 × 1010 2.28 × 1010 6.59 × 1010 4.8 × 109 1.3 × 1010
rank 1 10 4 13 2 11 6 3 8 9 12 5 7
C17-F13 mean 44,203.5 7.73 × 109 102,552.1 4.46 × 1010 70,549.51 2.06 × 1010 8.69 × 108 440,253.3 1.66 × 109 4.43 × 109 9.98 × 109 1.63 × 108 1.74 × 108
best 39,417.16 2.91 × 109 72,417.29 3.45 × 1010 39,047.23 1.37 × 1010 4.27 × 108 385,351.8 3490,814 1.73 × 109 8.96 × 109 63,314.68 61,879,640
worst 47,640.75 1.2 × 1010 139,843.7 5.05 × 1010 89,174.52 3.1 × 1010 1.71 × 109 549,081.5 5.13 × 109 7.98 × 109 1.11 × 1010 5.76 × 108 2.79 × 108
std 3447.109 4.32 × 109 28,590.46 7.42 × 109 23,479.33 7.5 × 109 5.8 × 108 73,870.14 2.35 × 109 2.61 × 109 9.87 × 108 2.76 × 108 92177490
median 44,878.03 8.02 × 109 98,973.74 4.67 × 1010 76,988.15 1.88 × 1010 6.72 × 108 413,289.9 7.45 × 108 4.01 × 109 9.92 × 109 38354572 1.78 × 108
rank 1 10 3 13 2 12 7 4 8 9 11 5 6
C17-F14 mean 38,247.02 8,398,313 6,983,904 83,370,942 37,992.77 7574,523 23,051,859 2,406,385 7,632,300 12,005,340 8,966,839 3,232,258 16,151,979
best 19,691.01 5,689,698 4,235,073 76,038,636 19,526.17 3959,310 16,617,918 1,206,786 4,435,632 8,814,373 6,670,450 720,653 10,615,559
worst 70,208.67 11,219,705 11,593,673 91,264,970 69,787.65 15,774,376 35,953,797 4,757,866 13,293,148 15,067,242 14,374,476 7,262,728 21,599,852
std 22,041.78 2,526,169 3,241,606 7,314,111 21,928.96 5,505,061 8787,473 1,618,096 3,949,408 2,628,175 3,652,301 2,811,928 4561,649
median 31,544.2 8,341,924 6,053,435 83,090,081 31,328.63 5,282,204 19,817,861 1,830,443 6,400,211 12,069,874 7,411,215 2,472,826 16,196,252
rank 2 8 5 13 1 6 12 3 7 10 9 4 11
C17-F15 mean 33,097.94 4.19 × 108 88,181.73 2.46 × 1010 34,635.7 1.03 × 1010 1.95 × 108 145,183.4 2.72 × 108 7.94 × 108 1.72 × 109 1.18 × 109 9,645,827
best 16,382.21 23,910,679 72,089.62 1.76 × 1010 17,471.38 6.25 × 109 69,888,989 80,674.01 1.24 × 108 4.89 × 108 5.36 × 108 58117.71 6,699,332
worst 44,575.1 1.22 × 109 110,726.8 3.07 × 1010 48,568.52 1.53 × 1010 4.94 × 108 208,724.2 5.69 × 108 1.14 × 109 4.14 × 109 2.91 × 109 12,373,368
std 13,525.92 5.44 × 108 18,472.61 6.5 × 109 14,309.74 3.92 × 109 2.01 × 108 53,444.25 2.01 × 108 2.9 × 108 1.64 × 109 1.44 × 109 2,319,862
median 35,717.23 2.16 × 108 84,955.27 2.51 × 1010 36,251.46 9.75 × 109 1.07 × 108 145,667.7 1.98 × 108 7.73 × 108 1.11 × 109 9.01 × 108 9,755,304
rank 1 8 3 13 2 12 6 4 7 9 11 10 5
C17-F16 mean 5289.667 8075.619 7346.94 23,585.12 5556.754 12,659.13 16,572.81 6401.656 6685.502 12,217.08 10,417.54 6132.963 11,108.18
best 4897.6 7396.592 6037.364 18,423.11 4859.187 11,295.55 13,966.61 5961.599 6185.134 10,721.76 9217.053 5449.275 9424.787
worst 5710.276 8970.729 8134.842 26,458.22 6867.361 14,021.14 18,721.12 6668.897 7453.341 13,860.22 11,540.53 6832.967 11,940.21
std 332.3395 704.2064 923.0135 3635.585 892.9725 1121.277 1963.62 327.4517 604.6548 1289.506 962.7863 582.5351 1138.671
median 5275.395 7967.578 7607.778 24,729.57 5250.235 12,659.92 16,801.76 6488.063 6551.766 12,143.17 10,456.29 6124.805 11,533.86
rank 1 7 6 13 2 11 12 4 5 10 8 3 9
C17-F17 mean 4400.558 10,409.14 5990.338 8,696,852 4366.873 151,808.6 15,333.77 5168.306 5408.623 9341.009 228,490.8 7064.66 6756.812
best 4055.441 5815.1 5796.742 2,357,254 4026.543 32,785.66 11,709.25 4917.866 4332.309 8097.868 42,794.52 6170.799 6191.594
worst 4671.854 16,795.95 6476.642 20,011,852 4628.367 375,453 18,769.63 5547.375 6488.278 10,527.61 741,374.4 7828.836 7423.221
std 260.7233 4852.693 326.2353 8,306,042 255.0694 158,483.7 3908.91 267.6024 896.4995 999.1039 342,134.4 692.6501 514.2877
median 4437.468 9512.766 5843.985 6,209,152 4406.292 99,497.89 15,428.1 5103.992 5406.953 9369.278 64,897.14 7129.502 6706.217
rank 2 9 5 13 1 11 10 3 4 8 12 7 6
C17-F18 mean 188,979.9 7,212,606 2,951,049 1.08 × 108 235,943.2 18,747,096 20,370,306 3,891,643 9,340,657 20,568,868 8,970,756 2,463,637 7,316,713
best 168,960.2 2,281,779 1,467,407 41,911,753 178,664.2 9,857,550 12,477,291 2,117,331 2,729,394 12,444,228 4,277,344 834,378.1 5,157,171
worst 217,287.5 14,425,982 4,665,842 1.97 × 108 379,813 28,848,858 31,924,135 7,854,026 15,928,695 38,379,799 11,074,720 3,768,395 10,061,294
std 22,970 5,140,198 1,449,149 65,562,281 96,626.92 7,801,882 8256,895 2,663,425 5,635,043 12,131,498 3,152,116 1,271,998 2,343,646
median 184,836 6071,331 2,835,474 96,283,852 192,647.90 18,140,988 18,539,900 2,797,608 9,352,270 15,725,723 10,265,479 2,625,888 7,024,194
rank 1 6 4 13 2 10 11 5 9 12 8 3 7
C17-F19 mean 240,362.6 8.76 × 108 3,017,804 2.34 × 1010 253,780.5 6.88 × 109 1.99 × 108 19,860,187 5.05 × 108 9.51 × 108 1.38 × 109 5.71 × 108 15,651,499
best 106,471.1 33,323,526 1,155,276 1.71 × 1010 112,995.9 6.17 × 109 73469347 6,784,792 13,099,458 4.24 × 108 5.24 × 108 1420743 5,304,591
worst 317,561.9 2.12 × 109 5,555,441 2.92 × 1010 335,639.9 8.01 × 109 3.14 × 108 31,723,596 1.91 × 109 1.98 × 109 2.57 × 109 1.49 × 109 35,863,459
std 92,219.0 9.6 × 108 1,859,799 4.98 × 109 97,113.3 8.03 × 108 1.01 × 108 10,221,012 9.38 × 108 6.96 × 108 9.4 × 108 6.8 × 108 14,375,122
median 268,708.6 6.73 × 108 2,680,249 2.37 × 1010 283,243.1 6.67 × 109 2.05 × 108 20,466,180 48,052,465 7.03 × 108 1.22 × 109 3.96 × 108 10,718,973
rank 1 9 3 13 2 12 6 5 7 10 11 8 4
C17-F20 mean 4329.037 5209.792 6336.396 7771.453 4716.199 7113.265 6925.121 5395.872 4996.863 7387.463 5974.363 5170.578 6642.64
best 3983.977 4821.265 5904.681 7612.301 4388.633 6767.715 6587.829 5094.733 4850.608 7234.322 5242.187 4710.582 6076.979
worst 4539.248 5659.555 6676.751 7841.025 4978.188 7576.378 7332.808 5543.659 5163.653 7497.733 6314.946 5782.027 7037.92
std 240.729 355.8995 343.9901 106.793 252.3931 386.9691 368.0945 203.5619 148.5221 125.1266 496.6382 474.2739 420.3355
median 4396.461 5179.175 6382.075 7816.242 4748.988 7054.484 6889.924 5472.548 4986.596 7408.899 6170.159 5094.852 6727.831
rank 1 5 8 13 2 11 10 6 3 12 7 4 9
C17-F21 mean 2736.167 3745.407 3729.792 4508.594 2838.871 4334.393 4315.533 3017.185 3055.55 3655.302 4547.086 3650.019 3629.856
best 2679.86 3690.774 3506.549 4427.007 2768.495 4120.796 3872.558 2972.154 2900.463 3567.526 4387.706 3423.076 3557.698
worst 2813.182 3796.665 3875.17 4568.519 2890.906 4510.86 4750.77 3054.39 3136.03 3719.88 4719.22 3851.77 3712.51
std 58.0787 43.77476 159.0511 61.58535 58.50085 166.9908 385.4136 35.2477 105.7954 70.19626 135.5839 178.1641 71.99652
median 2725.81 3747.09 3768.73 4519.43 2848.04 4352.96 4319.40 3021.10 3092.85 3666.90 4540.71 3662.61 3624.61
rank 1 9 8 12 2 11 10 3 4 7 13 6 5
C17-F22 mean 16,754.43 22,635.78 20,677.34 34,479.41 19,077.25 32,106.98 30,302.25 19,243.96 18,528.36 34,487.37 20,703.73 20,184.32 29,011.38
best 15,651.14 21,193.53 19,202.46 34,027.03 18,107.02 29,368.93 29,139.08 17,859.86 17,156.79 33,489 19,451.88 17,961.85 28,178.06
worst 17,268.55 23,665.76 22,710.46 35,121.42 20,362.55 33,216.89 31,342.78 20,447.75 19,437 35,320.04 21,879.51 21,096.56 30,184.34
std 754.6418 1037.438 1555.121 491.9479 953.8498 1830.945 1029.101 1331.092 1001.715 894.5323 1039.709 1497.787 894.7833
median 17,049.01 22,841.92 20,398.22 34,384.6 18,919.72 32,921.05 30,363.58 19,334.13 18,759.82 34,570.22 20,741.76 20,839.44 28,841.56
rank 1 8 6 12 3 11 10 4 2 13 7 5 9
C17-F23 mean 3330.207 5009.335 4180.505 5475.558 3302.335 5508.514 5381.020 3553.843 3630.727 4364.402 7806.769 5035.024 4491.184
best 3220.897 4915.96 4094.759 5190.584 3192.09 5331.809 5167.214 3462.843 3529.972 4221.49 7299.394 4779.893 4285.936
worst 3407.188 5150.114 4271.186 5700.211 3376.761 5801.627 5828.837 3670.808 3713.651 4491.014 8053.976 5209.153 4806.089
std 84.12463 101.5099 83.55801 210.9503 83.8719 203.2764 302.6356 90.02939 75.82554 126.8273 353.6352 191.2664 233.4911
median 3346.372 4985.632 4178.037 5505.718 3320.244 5450.31 5264.014 3540.861 3639.643 4372.552 7936.852 5075.525 4436.355
rank 2 8 5 11 1 12 10 3 4 6 13 9 7
C17-F24 mean 3838.394 6619.833 5501.153 10,952.73 4019.698 7130.901 6669.652 4156.191 4463.04 4946.4 10,577.72 6083.567 5573.038
best 3804.994 6393.899 5264.016 7257.544 3965.063 6181.58 5802.949 3992.141 4329.01 4779.776 10,344.84 6038.202 5498.956
worst 3880.947 6956.558 5697.902 13,415.8 4076.189 7864.329 7222.435 4387.281 4672.438 5127.243 10,849.330 6123.814 5654.398
std 33.5964 240.8529 193.1216 2980.522 55.04538 703.9283 626.4185 170.6274 146.9678 153.8419 268.4815 40.94055 69.16896
median 3833.817 6564.438 5521.346 11,568.79 4018.771 7238.848 6826.611 4122.67 4425.356 4939.289 10,558.35 6086.125 5569.398
rank 1 9 6 13 2 11 10 3 4 5 12 8 7
C17-F25 mean 3419.878 12,914.68 4200.03 22,463.79 3727.179 10,109.35 7602.511 3458.415 6612.48 9840.617 13,003.17 6315.64 8226.567
best 3270.776 10,959.75 3793.055 20,802.69 3639.544 7389.433 7500.673 3391.467 5802.505 7855.257 11,232.45 5406.982 7683.57
worst 3570.643 15,484.74 4584.833 26,151.87 3817.394 12,792.82 7828.874 3519.4 7077.109 13,190.3 14,733.21 7810.14 8659.75
std 127.2128 2106.496 327.3314 2514.302 84.07639 2611.297 152.0693 67.05617 559.221 2384.22 1600.964 1069.279 439.551
median 3419.046 12,607.12 4211.116 21,450.29 3725.889 10,127.58 7540.248 3461.397 6785.152 9158.458 13,023.5 6022.719 8281.474
rank 1 11 4 13 3 10 7 2 6 9 12 5 8
C17-F26 mean 12,161.53 33,589.15 25,812.52 47,915.4 12,417.5 36,882.86 39,697.02 13,011.43 16,796.16 26,337.9 36,037.68 26,179.06 23,813.48
best 11,570.58 32,040.89 22,771.24 45,204.13 12,010.75 34,702.39 36,284.73 12,173.32 16,104.17 23,268.42 34,617.49 23,436.07 18,794.69
worst 13,140.16 35,062.47 28,918.45 49,592 13,166.37 39,236.38 46,080.27 14,038 18,257.86 31,568.31 38,296.26 29,012.3 30,130.64
std 714.7895 1291.344 2627.91 2110.57 517.0592 2305.593 4571.018 774.4961 986.1479 3755.775 1584.211 2288.35 5129.716
median 11,967.7 33,626.62 25,780.19 48,432.75 12,246.44 36,796.33 38,211.53 12,917.19 16,411.3 25,257.43 35,618.49 26,133.95 23,164.3
rank 1 9 6 13 2 11 12 3 4 8 10 7 5
C17-F27 mean 3573.983 7203.719 4220.107 12,874.15 3543.702 6590.686 5549.819 3636.355 4351.534 4365.099 14,390.47 4068.458 5427.951
best 3550.019 6374.999 4035.689 9574.128 3515.753 5450.785 5255.732 3538.111 4047.274 4231.086 12,460.66 3698.791 5163.581
worst 3617.97 8029.224 4525.976 16,299.41 3586.981 7337.146 6286.109 3743.107 4728.147 4538.464 16,773.18 4534.344 5728.043
std 30.36471 874.2169 212.0854 3625.498 30.41211 825.7145 492.4035 87.09758 298.1583 144.9164 1847.757 369.1118 238.5253
median 3563.971 7205.326 4159.381 12,811.52 3536.036 6787.406 5328.717 3632.1 4315.358 4345.422 14,164.01 4020.349 5410.089
rank 2 11 5 12 1 10 9 3 6 7 13 4 8
C17-F28 mean 3582.808 16,810.98 4799.097 29,879.23 3850.162 16,533.6 11,426.62 3532.959 10765.53 11,980.69 17,423.16 6348.414 13,091.11
best 3420.284 15,333.26 4474.553 26,738.46 3777.292 14,884.29 9122.899 3454.509 8221.553 9544.848 15,852.57 4956.941 12,054.66
worst 3659.831 18,085.58 5038.336 33,810.2 3972.019 18,597.99 13,140.11 3636.308 14,812.54 14,940.48 19,363.45 7865.142 14,211.12
std 110.8076 1313.643 238.6427 2965.76 86.65758 1651.567 1959.457 75.76293 2827.535 2230.037 1666.674 1328.374 1159.838
median 3625.557 16,912.53 4841.749 29,484.12 3825.668 16,326.07 11,721.74 3520.51 10,014.01 11,718.71 17,238.3 6285.787 13,049.32
rank 2 11 4 13 3 10 7 1 6 8 12 5 9
C17-F29 mean 6785.358 11,200.52 9945.999 371,294.3 7011.439 29,447.41 16,930.69 8701.23 8650.05 14,358.73 21,205.48 8372.447 12,438.74
best 6237.576 10,204.3 8591.844 199,089.7 6512.523 15,174.79 13,802.42 7941.767 7491.625 13,504.12 16,011.96 7665.661 12,035.03
worst 7296.052 11,863.42 10,788.87 515,537.6 7399.818 66,248.24 21,278.25 9252.116 10,249.87 15,398.75 24,203.99 8683.496 13,143.18
std 489.398 754.6761 947.033 134,866.2 422.6678 24,574.85 3132.304 552.0585 1345.612 871.218 3595.977 482.8703 485.136
median 6803.901 11,367.19 10,201.64 385,275.00 7066.708 18,183.31 16,321.06 8805.519 8429.351 14,266.02 22,302.99 8570.316 12,288.36
rank 1 7 6 13 2 12 10 5 4 9 11 3 8
C17-F30 mean 5,554,314 2.47 × 109 29,428,850 4 × 1010 6,188,795 1.46 × 1010 1.17 × 109 1.19 × 108 2.32 × 109 3.05 × 109 1.18 × 1010 3.93 × 108 6.24 × 108
best 2,780,134 1.38 × 108 16,769,683 3.74 × 1010 2,886,968 1.32 × 1010 8.85 × 108 85,223,927 5.3 × 108 1.18 × 109 8.16 × 109 7358589 4.39 × 108
worst 7,910,687 6.19 × 109 51,751,386 4.33 × 1010 8,330,799 1.64 × 1010 1.6 × 109 1.65 × 108 5.4 × 109 4.23 × 109 1.56 × 1010 1.52 × 109 1.04 × 109
std 2,148,328 2.6 × 109 15,661,651 2.53 × 109 2,560,052 1.43 × 109 3.08 × 108 34,020,142 2.12 × 109 1.31 × 109 3.05 × 109 7.51 × 108 2.83 × 108
median 5,763,217 1.77 × 109 24,597,166 3.97 × 1010 6,768,707 1.45 × 1010 1.1 × 109 1.13 × 108 1.68 × 109 3.4 × 109 1.17 × 1010 22,288,328 5.08 × 108
rank 1 9 3 13 2 12 7 4 8 10 11 5 6
Sum rank 35 244 144 359 61 318 275 116 159 255 281 172 220
Mean rank 1.206897 8.413793 4.965517 12.37931 2.103448 10.96552 9.482759 4 5.482759 8.793103 9.689655 5.931034 7.586207
Total rank 1 8 4 13 2 12 10 3 5 9 11 6 7

What can be concluded from the comparison of simulation results is that for the dimension d=10, SOA is the best optimizer in handling the functions C17-F3, C17-F6, C17-F7, C17-F10, C17-F19 to C17-F24, C17-F26 to C17-F30. For the dimension d=30, SOA is the best optimizer in handling the functions C17-F1, C17-F3 to C17-F5, C17-F7 to C17-F11, C17-F14 to C17-F16, C17-F20, C17-F21, C17-F23, C17-F26, C17-F27, C17-F29, and C17-F30. For the dimension d=50, SOA is the best optimizer in handling the functions C17-F1, C17-F3 to C17-F10, C17-F12 to C17-F20, C17-F22, C17-F23, and C17-F25, to C17-F30. For the dimension d=100, SOA is the best optimizer in handling the functions C17-F1, C17-F3 to C17-F5, C17-F7 to C17-F13, C17-F15, C17-F16, C17-F18, to C17-F22, C17-F24, to C17-F26, C17-F29, and C17-F30.

The optimization results show that the proposed SOA approach has provided superior performance compared to competing algorithms in the CEC 2017 test suite optimization by creating a suitable balance between exploration and exploitation. The performance of SOA and competitor algorithms in the optimization of the CEC 2017 test suite is drawn as a boxplot diagram in Figure 2, Figure 3, Figure 4 and Figure 5.

Figure 2.

Figure 2

Figure 2

Boxplot diagram of SOA and competitor algorithms performances on the CEC 2017 test suite (for the dimension d=10).

Figure 3.

Figure 3

Figure 3

Boxplot diagram of SOA and competitor algorithms performances on the CEC 2017 test suite (for the dimension d=30).

Figure 4.

Figure 4

Figure 4

Boxplot diagram of SOA and competitor algorithms performances on the CEC 2017 test suite (for the dimension d=50).

Figure 5.

Figure 5

Figure 5

Boxplot diagram of SOA and competitor algorithms performances on the CEC 2017 test suite (for the dimension d=100).

4.2. Evaluation the CEC 2019 Test Suite

This subsection tests the effectiveness of the proposed SOA approach and competing algorithms in solving the CEC 2019 test suite. The optimization results of C19-F1 to C19-F10 functions are published in Table 6.

Table 6.

Optimization results of the CEC 2019 test suite.

SOA WSO AVOA RSA MPA TSA WOA MVO GWO TLBO GSA PSO GA
C19-F1 mean 1 71,754.43 1 1 1 20,197.74 11,700,900 1,132,771 27,189.42 68.36027 6.2 × 108 149,550.8 7,917,670
best 1 1160.891 1 1 1 2.7537 2,455,600 376,289.6 1.003811 1.000003 1.49 × 108 14,365.34 2,787,375
worst 1 205,465.8 1 1 1 80,619 16,679,000 2,285,093 94,712.58 270.415 1.07 × 109 475,601.4 16,682,079
std 0 92,622.55 0 0 0 40,280.89 6,367,086 841,143.6 45,495.01 134.7032 4.66 × 108 218,241.3 6,534,856
median 1 40,195.5 1 1 1 84.6 13,834,500 934,851.2 7022.04 1.013028 6.33 × 108 54,118.3 6,100,613
rank 1 5 1 1 1 3 9 7 4 2 10 6 8
C19-F2 mean 3.1203 172.9367 4.694109 5 3.569175 800.59 6139.5 563.8434 454.4571 667.1054 27,745.11 363.9978 857.5801
best 2.607813 98.73351 4.303868 5 2.798006 629.09 2908 286.6219 210.5741 5.564019 9851.265 226.8182 577.9538
worst 3.596576 266.8291 5 5 4.344219 937.15 9275.1 838.1335 658.0928 1190.362 42,469.39 544.8626 1135.415
std 0.409111 70.34908 0.359864 5.13 × 10−16 0.631625 136.5541 2632.46 227.506 184.6327 537.804 14,988.08 133.4324 290.0151
median 3.138405 163.0922 4.736285 5 3.567238 818.06 6187.45 565.309 474.5807 736.2478 29,329.9 342.1552 858.4759
rank 1 5 3 4 2 10 12 8 7 9 13 6 11
C19-F3 mean 1.250139 1.892155 2.126998 8.138315 1.423922 6.45255 6.1394 8.960775 1.889948 4.716604 4.003168 3.777545 5.779726
best 1.045965 1.409789 1.409196 6.294517 1.196344 1.7408 3.0642 7.711774 1.141124 4.149536 2.763422 1.409135 3.599784
worst 1.468114 2.377011 3.342791 9.21189 1.563064 9.7143 9.6473 10.70855 3.407555 5.801678 5.911327 7.687041 7.700128
std 0.23558 0.555352 0.920308 1.299598 0.165362 3.397994 2.740517 1.498499 1.026228 0.751039 1.382805 3.010391 1.849209
median 1.243239 1.890909 1.878002 8.523426 1.46814 7.17755 5.92305 8.71139 1.505556 4.457601 3.668962 3.007002 5.909496
rank 1 4 5 12 2 11 10 13 3 8 7 6 9
C19-F4 mean 8.992048 17.42558 35.32589 73.96348 11.44685 53.1035 59.77375 25.557 23.2038 35.43137 51.99142 18.90922 22.35515
best 3.019184 13.93534 8.959667 55.8996 7.9647 41.459 32.984 22.89004 10.10581 32.68921 39.80328 10.94959 19.10672
worst 12.96868 21.89463 57.7123 94.37194 14.929 65.757 92.985 29.57352 38.80844 41.06531 60.69719 36.81838 27.48026
std 4.53174 4.092737 20.23611 16.55228 3.493927 11.06971 26.37413 2.951315 13.70501 3.931349 9.096213 12.04949 3.586093
median 9.990163 16.93617 37.31579 72.79118 11.44685 52.599 56.563 24.88222 21.95048 33.98547 53.73261 13.93446 21.41682
rank 1 3 8 13 2 11 12 7 6 9 10 4 5
C19-F5 mean 1.050836 1.688348 1.201342 88.27602 1.034475 29.61225 2.0399 1.392442 1.595406 2.934297 1.136918 1.213511 1.725773
best 1.047471 1.210439 1.10852 66.19828 1.0074 13.555 1.6941 1.239289 1.347328 2.63866 1.066225 1.179585 1.550766
worst 1.057175 2.265097 1.285169 108.9916 1.0616 62.067 2.3591 1.756175 1.893882 3.143506 1.205143 1.253634 1.841835
std 0.004577 0.456641 0.07586 17.49218 0.028578 22.85461 0.279808 0.246618 0.258445 0.225516 0.070591 0.038228 0.125116
median 1.049349 1.638929 1.205841 88.95708 1.03445 21.4135 2.0532 1.287153 1.570207 2.977511 1.138152 1.210412 1.755246
rank 2 8 4 13 1 12 10 6 7 11 3 5 9
C19-F6 mean 1.074498 2.901374 7.091154 9.942598 1.192698 7.857175 10.6821 3.023598 3.494285 4.576521 4.111191 3.643596 3.227866
best 1.036486 1.801215 6.214133 9.456187 1.074 4.3964 9.3754 1.226604 1.335962 3.587161 1.139357 1.531474 2.490765
worst 1.179165 3.603571 9.322565 10.7512 1.321624 10.543 11.969 4.363759 4.995392 5.230096 5.652704 6.240727 4.391409
std 0.06988 0.794252 1.496419 0.606401 0.104412 2.598436 1.062426 1.370934 1.548655 0.722828 2.109974 1.980984 0.835364
median 1.04117 3.100355 6.41396 9.781504 1.187584 8.24465 10.692 3.252014 3.822894 4.744412 4.826352 3.401092 3.014646
rank 1 3 10 12 2 11 13 4 6 9 8 7 5
C19-F7 mean 246.8228 487.5351 1082.794 1730.98 302.0954 1406.9 1141.905 1056.615 1177.53 1175.092 1660.543 1151.383 707.8292
best 150.4273 282.8179 803.7554 1577.123 165.3973 1022 702.62 723.0297 1021.721 708.6485 1502.922 658.1489 490.5917
worst 328.0506 758.795 1546.282 1815.608 451.11 1685.7 1794.3 1850.827 1376.227 1521.911 1797.54 1606.777 1093.745
std 73.04863 211.9359 352.957 108.8781 117.496 279.3649 463.0885 533.2837 167.1757 370.338 133.3842 444.184 282.0167
median 254.4067 454.2637 990.5686 1765.594 295.9372 1459.95 1035.35 826.3016 1156.086 1234.905 1670.856 1170.303 623.4902
rank 1 3 6 13 2 11 7 5 10 9 12 8 4
C19-F8 mean 2.981774 3.730856 4.468653 4.818338 3.3539 4.1504 4.84945 4.059096 3.609261 4.301578 5.216925 4.608137 4.529276
best 2.825294 3.676426 3.927288 4.538189 3.010552 3.5611 4.607 3.561631 3.366284 4.055844 5.119708 4.369611 4.30402
worst 3.104412 3.84246 4.89483 4.985393 3.6811 4.9029 5.082 4.484265 4.036074 4.870075 5.373209 4.978318 4.669163
std 0.131505 0.07541 0.456051 0.200563 0.338951 0.562938 0.210516 0.436397 0.302651 0.381754 0.12212 0.264886 0.164295
median 2.998694 3.702269 4.526247 4.874885 3.361974 4.0688 4.8544 4.095245 3.517342 4.140198 5.187391 4.542309 4.571962
rank 1 4 8 11 2 6 12 5 3 7 13 10 9
C19-F9 mean 1.081897 1.175838 1.393224 3.105656 1.092347 1.350775 1.3803 1.176442 1.220459 1.324073 1.196267 1.193862 1.138063
best 1.063102 1.122186 1.078336 2.401267 1.0512 1.1981 1.1917 1.150186 1.1062 1.253609 1.078801 1.089627 1.11366
worst 1.115502 1.242474 1.604168 3.684131 1.123 1.5607 1.6508 1.203633 1.355802 1.384995 1.315911 1.263166 1.184152
std 0.024024 0.054244 0.22406 0.546042 0.033978 0.161533 0.21688 0.024786 0.113289 0.06944 0.11506 0.075043 0.031644
median 1.074491 1.169346 1.445197 3.168613 1.097595 1.32215 1.33935 1.175974 1.209917 1.328844 1.195178 1.211327 1.12722
rank 1 4 12 13 2 10 11 5 8 9 7 6 3
C19-F10 mean 18.03383 17.89517 21.03628 21.46784 21.00075 21.41375 21.212 21.02743 21.47564 21.43069 23.24989 21.03227 21.26732
best 6.811592 7.37422 20.97165 21.37514 21 21.355 21.047 21.00739 21.46041 21.39861 20.99799 20.99969 21.10764
worst 22.01547 21.54158 21.17207 21.54733 21.003 21.538 21.594 21.04061 21.49669 21.50204 24.54712 21.12946 21.39193
std 7.483952 7.014666 0.091558 0.070798 0.0015 0.084215 0.256657 0.014164 0.017614 0.048814 1.666164 0.064791 0.126423
median 21.65414 21.33245 21.0007 21.47445 21 21.381 21.1035 21.03087 21.47273 21.41107 23.72722 20.99997 21.28486
rank 2 1 6 11 3 9 7 4 12 10 13 5 8
Sum rank 12 40 63 103 19 94 103 64 66 83 96 63 71
Mean rank 1.2 4 6.3 10.3 1.9 9.4 10.3 6.4 6.6 8.3 9.6 6.3 7.1
Total rank 1 3 4 11 2 9 11 5 6 8 10 4 7

What is evident from the comparison of the simulation results is that the proposed SOA approach is the first best optimizer C19-F1 to C19-F4, and C19-F6 to C19-F9 functions against competitor algorithms. The optimization results show that SOA’s proposed approach better handles the CEC 2019 test suite by winning the first rank compared to competitor algorithms. The performance of SOA and competitor algorithms in the optimization of the CEC 2019 test suite is drawn as a boxplot diagram in Figure 6.

Figure 6.

Figure 6

Boxplot diagram of SOA and competitor algorithms performances on the CEC 2019 test suite.

4.3. Statistical Analysis

In this subsection, by providing a statistical analysis of the simulation results, it has been investigated how significant the superiority of the proposed SOA approach is against competitor algorithms from a statistical point of view. For this reason, the Wilcoxon rank sum test [56] is utilized, which is applicable to determine the significant difference between the average of two data samples. The results of applying the Wilcoxon rank sum test on the performance of the proposed SOA proposed approach and competitor algorithms are reported in Table 7. Based on the values obtained for the p-value index, in cases where the p-value is less than 0.05, the proposed SOA approach has a statistically significant superiority compared to the corresponding competitor algorithm.

Table 7.

Wilcoxon rank sum test results.

Compared Algorithm Types of Objective Functions
CEC 2017 CEC 2019
d=10 d=30 d=50 d=100
SOA vs. WSO 1.93 × 10−15 2.02 × 10−21 2.02 × 10−21 1.97 × 10−21 2.63 × 10−7
SOA vs. AVOA 6.1 × 10−20 1.16 × 10−20 1.97 × 10−21 1.97 × 10−21 2.07 × 10−5
SOA vs. RSA 2.02 × 10−21 1.97 × 10−21 1.97 × 10−21 1.97 × 10−21 2.79 × 10−7
SOA vs. MPA 0.025318 1.36 × 10−5 1.86 × 10−12 1.74 × 10−15 0.000237
SOA vs. TSA 2.24 × 10−21 1.97 × 10−21 1.97 × 10−21 1.97 × 10−21 1.18 × 10−7
SOA vs. WOA 1.97 × 10−21 1.97 × 10−21 1.97 × 10−21 1.97 × 10−21 1.48 × 10−7
SOA vs. MVO 2.77 × 10−19 5.13 × 10−19 1.56 × 10−20 2.8 × 10−20 4.98 × 10−7
SOA vs. GWO 7.23 × 10−20 4.62 × 10−21 3.69 × 10−21 4.74 × 10−21 1.71 × 10−6
SOA vs. TLBO 3.78 × 10−21 1.97 × 10−21 1.97 × 10−21 1.97 × 10−21 1.97 × 10−7
SOA vs. GSA 7.23 × 10−20 1.97 × 10−21 2.73 × 10−21 1.97 × 10−21 3.57 × 10−8
SOA vs. PSO 2.42 × 10−20 7.79 × 10−21 2.07 × 10−21 1.97 × 10−21 7.06 × 10−7
SOA vs. GA 4.18 × 10−21 2.02 × 10−21 1.97 × 10−21 1.97 × 10−21 1.71 × 10−7

5. SOA for Real-World Applications

This section is dedicated to analyzing the effectiveness of the proposed SOA approach in handling real-world applications. In this regard, SOA and competitor algorithms are employed to optimize the CEC 2011 test suite and four engineering design problems.

5.1. Evaluation the CEC 2011 Test Suite

This collection contains twenty-two real-world optimization problems (the C11-F3 function was excluded in the simulation studies). The CEC 2011 test suite details are described in [57]. The optimization results of the CEC 2011 test suite using SOA and competitor algorithms are published in Table 8.

Table 8.

Optimization results of the CEC 2011 test suite.

SOA WSO AVOA RSA MPA TSA WOA MVO GWO TLBO GSA PSO GA
C11-F1 mean 3.703267 15.02557 25.74562 26.00412 4.069952 17.52275 21.89831 13.4942 15.568 20.13739 25.86975 21.49811 25.49193
best 2.68 × 10−10 11.75673 24.83901 25.15683 2.85 × 10−10 8.510385 17.24132 6.548961 10.72236 17.39148 24.1914 17.49104 24.75272
worst 14.81307 19.29177 26.94225 27.78769 16.27981 21.63138 24.82611 16.5131 22.07106 22.56158 27.76547 25.58579 26.07053
std 7.406534 3.129599 1.051112 1.209479 8.139905 6.077377 3.257521 4.67819 5.389997 2.179018 1.524199 3.753819 0.558841
median 1.37 × 10−9 14.52688 25.60061 25.53597 1.48 × 10−9 19.97462 22.7629 15.45736 14.7393 20.29825 25.76107 21.45781 25.57223
rank 1 4 11 13 2 6 9 3 5 7 12 8 10
C11-F2 mean −25.5074 −22.3944 −11.6301 −8.06028 −24.8695 −6.49474 −15.4353 −9.34108 −21.6587 −8.61104 −9.40185 −22.0875 −13.1955
best −26.343 −22.8813 −14.0599 −8.64276 −25.7669 −9.42193 −20.4428 −12.3034 −24.5033 −9.39253 −13.4981 −24.4758 −14.0636
worst −24.2869 −21.4054 −9.06418 −7.42364 −23.6464 −4.02889 −11.7159 −7.01703 −15.7941 −7.55467 −6.03461 −19.675 −12.6002
std 1.004079 0.674967 2.043459 0.550565 0.996461 2.542635 4.065062 2.333323 3.960315 0.858825 3.099445 2.334602 0.625598
median −25.6998 −22.6454 −11.6981 −8.08736 −25.0324 −6.26406 −14.7912 −9.02192 −23.1687 −8.74848 −9.03735 −22.0996 −13.0591
rank 1 3 8 12 2 13 6 10 5 11 9 4 7
C11-F4 mean −34.1366 −29.4024 −17.5227 −16.7272 −33.0629 −27.8822 −23.8592 −27.1652 −31.4271 −14.1604 −26.2837 −7.58 −8.27727
best −34.4821 −33.8574 −19.4025 −19.341 −34.2193 −31.2664 −27.0822 −31.5712 −34.2156 −20.773 −34.1647 −11.3148 −12.0614
worst −33.4793 −27.2841 −16.1919 −13.8236 −31.812 −25.793 −21.0792 −24.2788 −26.2364 −10.1154 −21.2736 −3.0134 −4.22734
std 0.452345 3.068482 1.37731 2.848936 0.998888 2.51344 2.466816 3.106749 3.57637 4.888331 5.749063 3.428548 3.376156
median −34.2925 −28.234 −17.2482 −16.8722 −33.1102 −27.2347 −23.6377 −26.4055 −32.6282 −12.8767 −24.8482 −7.99588 −8.41014
rank 1 4 9 10 2 5 8 6 3 11 7 13 12
C11-F5 mean −27.1938 −19.3848 −10.0921 −10.5136 −25.6126 −12.3726 −14.1942 0 −22.2141 −5.21334 −14.2828 0 0
best −27.4298 −23.0059 −14.7254 −11.5854 −26.5001 −19.429 −15.0878 0 −26.8272 −12.1923 −16.9124 0 0
worst −26.4862 −16.8457 −7.09818 −9.51564 −23.0059 0 −12.4219 0 −19.5116 0 −10.6775 0 0
std 0.471752 2.647173 3.382754 1.153367 1.73799 8.505039 1.25671 0 3.488744 6.19006 3.109174 0 0
median −27.4297 −18.8438 −9.27249 −10.4768 −26.4723 −15.0308 −14.6336 0 −21.2588 −4.33054 −14.7707 0 0
rank 1 4 9 8 2 7 6 11 3 10 5 11 11
C11-F6 mean 0.89073 1.14754 2.024755 2.155071 0.90234 1.643725 2.052031 0.965717 1.048196 1.874535 1.082047 1.180848 2.052041
best 0.866406 0.998087 1.6614 1.83069 0.841922 1.560405 1.793715 0.833545 0.938764 1.614306 0.905594 1.008846 1.855107
worst 0.934629 1.258533 2.187947 2.345592 0.966592 1.831218 2.309743 1.247127 1.146828 2.007636 1.387668 1.423934 2.215405
std 0.030907 0.129835 0.247021 0.227085 0.053749 0.125878 0.234016 0.190355 0.085177 0.17657 0.224094 0.176804 0.15728
median 0.880943 1.16677 2.124836 2.222001 0.900423 1.591638 2.052333 0.891097 1.053595 1.938099 1.017464 1.145306 2.068825
rank 1 6 10 13 2 8 11 3 4 9 5 7 12
C11-F7 mean 231.7975 223.6592 276.5 349.25 220 234 291.25 220 224.5 227 231.5 329.9552 229.8177
best 220 220 230 299 220 220 238 220 220 220 220 220 220
worst 239.4414 234.6368 323 404 220 258 333 220 238 238 248 535.8208 259.2707
std 8.387818 7.318376 40.02083 43.06874 0 18.11077 39.55903 0 9 8.717798 13.89244 141.2683 19.63537
median 233.8743 220 276.5 347 220 229 297 220 220 225 229 282 220
rank 7 2 9 12 1 8 10 1 3 4 6 11 5
C11-F8 mean 7306.049 735,450.4 1,029,600 1301,689 7878.018 96,263.48 401,545.2 127,251.3 29,143.13 549,851 998,962.5 1,637,763 2,186,754
best 4355.355 547,467.2 914,559 848,186.4 4665.333 69,896.59 323,827.5 88,847.38 17,099.15 377,823.8 955,606.7 616,975.9 2,097,586
worst 11,321.75 873,535.9 1,112,084 1,528,229 12,237.1 134,708.9 547,008.1 164,393.9 42,638.2 747,382 1,052,476 3,466,500 2,273,623
std 3118.179 147,088.4 86,808.81 308,299.6 3430.68 27,889.49 103,098.1 30,939.54 12,355.31 152,022.1 42,600.87 1256,071 72,053.94
median 6773.544 760,399.2 1,045,878 1,415,170 7304.821 90,224.2 367,672.5 127,881.9 28,417.59 537,099 993,883.9 1,233,788 2,187,904
rank 1 8 10 11 2 4 6 5 3 7 9 12 13
C11-F9 mean −21.1519 −16.4886 −8.89083 −10.1972 −19.7224 −12.2849 −9.69672 −17.4831 −11.0572 −10.2549 −11.3843 −10.2803 −10.0705
best −21.5356 −18.7915 −9.07622 −10.5958 −20.7818 −15.2414 −10.2871 −21.2049 −12.9979 −10.2865 −11.8241 −10.364 −10.1474
worst −20.6824 −14.5174 −8.70287 −9.81793 −16.9694 −10.5739 −8.59883 −12.3942 −10.3885 −10.2262 −10.935 −10.2224 −9.99439
std 0.418453 2.099664 0.19497 0.317858 1.843503 2.110651 0.788387 4.054017 1.294026 0.027217 0.446827 0.06044 0.066287
median −21.1947 −16.3228 −8.89211 −10.1875 −20.5693 −11.6621 −9.95046 −18.1667 −10.4213 −10.2535 −11.389 −10.2674 −10.0701
rank 1 4 13 10 2 5 12 3 7 9 6 8 11
C11-F10 mean 275,953.6 293,843.2 1,728,003 10,733,179 507,841.1 6814,247 1668,923 1969,755 4265,332 5,689,705 1,570,136 5710,499 6,730,921
best 111,906.1 119,680.6 1,671,593 10,440,242 443,295.4 5637,001 1596,987 1584,500 3731,297 5,689,705 1,439,379 5689,705 6,711,548
worst 435,202.3 457,974.2 1,774,439 10,907,934 577,384.2 8,101,877 1718,805 2559,982 4585,233 5,689,705 1,703,594 5748,435 6,752,137
std 133,300.2 140,150.7 43,954.16 203,662.6 57,922.72 1,169,664 51,360.73 465,329.2 378,888.6 0 128,768.8 27,792.26 17,639.59
median 278,353 298,858.9 1,732,991 10,792,271 505,342.4 6,759,054 1,679,950 1,867,268 4,372,400 5,689,705 1,568,786 5,701,929 6,729,999
rank 1 2 6 13 3 12 5 7 8 9 4 10 11
C11-F11 mean 1244,166 3917,084 7200,862 15,954,845 1,205,197 6,003,707 6,372,956 1,356,302 1,588,951 15,505,519 6777,124 2,450,810 15,381,122
best 1115,988 3701,366 6,994,873 14,807,307 1,087,931 4,992,934 5,869,317 1,237,960 1,378,205 14,999,220 6594,614 2,214,801 14,242,937
worst 1331,317 4098,419 7,301,082 16,959,124 1,287,550 7,191,303 6,835,128 1,627,660 2,025,660 15,937,381 7026,405 2,558,421 16,446,911
std 91,442.38 176,574.8 139,296.1 882,680.7 84,212.59 903,553.7 417,842.9 184,571.9 300,145.8 397,440.9 207,663.9 158,822.7 935,503.1
median 1,264,680 3,934,275 7,253,747 16,026,475 1,222,653 5,915,295 6,393,689 1,279,795 1,475,969 15,542,737 6,743,739 2,515,010 15,417,320
rank 2 6 10 13 1 7 8 3 4 12 9 5 11
C11-F12 mean 15,444.2 15,775.42 15,454.67 16,506.66 16,390.34 15,566.71 15,506.98 15,488.7 15,519.23 15,935.78 129,995.2 15,515.88 16,052.38
best 15,444.19 15,444.23 15,451.9 15,996.18 15,444.21 15,529.77 15,484.73 15,469.18 15,500.74 15,514.42 113,048.8 15,477.7 15,489.97
worst 15,444.21 16,732.14 15,457.72 17,774.94 16,966.72 15,613.13 15,533.89 15,505.51 15,547.46 16,670.71 151,977.1 15,555.92 17,025.63
std 0.010596 637.9726 2.451103 852.4752 667.7195 35.95627 24.013 14.9133 20.19086 541.7847 16,644.88 33.017 694.0509
median 15,444.19 15,462.66 15,454.53 16,127.77 16,575.22 15,561.97 15,504.65 15,490.05 15,514.36 15,778.99 127477.5 15,514.94 15,846.96
rank 1 8 2 12 11 7 4 3 6 9 13 5 10
C11-F13 mean 18,808.95 18,401.87 18,913.78 276,941.8 18,308.93 19,373.02 19,262.54 19,316.49 19,545.76 108,292.5 19,295.41 19,116.86 19,139.07
best 18,583.4 18,212.02 18,679.04 202,857.5 18,281.42 19,118.13 19,044.16 19,136.48 19,340.25 42,350.89 19,218.27 18,963.55 18,965.28
worst 18,941.42 18,524.11 19,086.98 400,961 18,342.71 19,749.48 19,529.18 19,493.59 19,714.25 254,303.9 19,414.24 19,255.93 19,268.32
std 156.5688 134.1286 181.804 88,734.65 31.09058 267.474 210.8087 146.6933 196.8206 98,161.29 84.17887 157.4519 144.5224
median 18,855.48 18,435.69 18,944.54 251,974.4 18,305.8 19,312.23 19,238.41 19,317.94 19,564.27 68,257.65 19,274.56 19,123.97 19,161.34
rank 3 2 4 13 1 10 7 9 11 12 8 5 6
C11-F14 mean 33,436.9 33,006.71 239,954.4 2,343,498 32,840.39 58,551.43 55,559.51 32,996.16 33,227.12 9,328,370 406,885.7 33,333.04 6,772,673
best 33,126.18 32,844.61 61,174.85 975,713.9 32,786.83 33,205.38 33,070.23 32,880.13 33,076.3 5,245,604 353,167.1 33,320.61 4,619,131
worst 33,831.7 33,126.57 439,827.3 6,129,448 32,874.34 133,374.7 122,653.1 33,127.33 33,382.38 13,754,921 429,323.5 33,357.17 10,429,108
std 309.7042 134.8848 203,421.2 2,527,893 37.99649 49,883.49 44,729.12 107.7502 132.081 3,483,336 36,212.51 17.05479 2,694,081
median 33,394.87 33,027.82 229,407.7 1,134,415 32,850.19 33,812.82 33,257.37 32,988.58 33,224.9 9,156,476 422,526.2 33,327.18 6,021,226
rank 6 3 9 11 1 8 7 2 4 13 10 5 12
C11-F15 mean 131,896.2 140,692.8 138,044.1 2362,861 141,030 139,185.7 149,714.5 142,078 137,989.1 98,216,083 16,661,057 82,739,645 90,489,805
best 129,599.2 134,258.9 134,145.7 551,007.8 136,822.8 134,983.1 143,326.3 137,708.7 134,926 81,712,714 145,480.7 67,023,611 77,222,102
worst 133,406.6 151,586.1 142,366.4 5916,825 143,594.4 144,166.6 156,177.1 149,494.5 143,091.5 1.11 × 108 42,521,588 1 × 108 1.04 × 108
std 1692.118 7711.282 3367.715 2,413,071 3052.919 3843.03 5629.417 5157.713 3897.759 12,641,427 18,783,856 16,142,420 11,527,058
median 132,289.6 138,463.1 137,832.2 1491,805 141,851.4 138,796.5 149,677.3 140,554.5 136,969.5 99,861,336 11,988,581 81,736,076 90,566,521
rank 1 5 3 9 6 4 8 7 2 13 10 11 12
C11-F16 mean 1,992,168 4,080,675 6.39 × 109 1.91 × 1010 1,931,384 1.7 × 109 1.12 × 1010 3,335,018 2,977,526 2.45 × 1010 1.37 × 1010 2.05 × 1010 2.24 × 1010
best 1,966,581 1,935,090 5.81 × 109 1.37 × 1010 1,899,652 9.95 × 108 8.91 × 109 2,994,846 2,450,995 1.85 × 1010 1.1 × 1010 1.67 × 1010 2.1 × 1010
worst 2,004,837 9,745,854 7 × 109 2.33 × 1010 1,956,433 2.5 × 109 1.29 × 1010 3,937,955 3,345,029 2.98 × 1010 1.55 × 1010 2.44 × 1010 2.39 × 1010
std 17,340.9 3,793,542 5.24 × 108 4.12 × 109 24,490.05 6.31 × 108 1.81 × 109 435,811.6 379,800.1 5.09 × 109 1.91 × 109 3.47 × 109 1.26 × 109
median 1,998,628 2,320,879 6.38 × 109 1.96 × 1010 1,934,726 1.66 × 109 1.15 × 1010 3,203,636 3,057,041 2.48 × 1010 1.41 × 1010 2.04 × 1010 2.24 × 1010
rank 2 5 7 10 1 6 8 4 3 13 9 11 12
C11-F17 mean 966,310.6 1,616,414 16,449,493 1.45 × 108 944,296.7 1909,746 12,427,380 986,840.3 1100,256 29,913,771 14,001,521 1.87 × 108 1.28 × 108
best 952,773.8 1,094,971 9,228,474 1 × 108 941,062.2 1271,774 4919,875 958,253.1 1018,907 26,861,276 11,017,330 1.75 × 108 1.26 × 108
worst 979,957.6 2,285,712 29,396,167 1.66 × 108 947,649.9 2280,117 25,716,414 1,030,102 1,340,216 37,140,318 17,250,112 2.03 × 108 1.32 × 108
std 11,741.73 494,288.8 9,390,234 30,701,419 2718.591 440,403.5 9,750,591 30,602.88 159,976.7 4,871,672 2,620,744 14,016,796 3,160,298
median 966,255.5 1,542,486 13,586,665 1.57 × 108 944,237.3 2,043,546 9,536,616 979,503 1,020,951 27,826,745 13,869,321 1.85 × 108 1.27 × 108
rank 2 5 9 12 1 6 7 3 4 10 8 13 11
C11-F18 mean 1,000,924 2,590,116 16,582,334 1.42 × 108 1,069,181 2,937,110 14,575,361 1,710,525 1,589,011 35,041,852 15,310,972 1.81 × 108 1.27 × 108
best 943,538.7 1,954,981 14,730,898 1.23 × 108 997,145.1 2,414,231 5831,462 1,393,338 1,167,771 26,831,644 9,362,833 1.66 × 108 1.26 × 108
worst 1,061,517 3,891,235 20,548,870 1.79 × 108 1130,546 3,393,560 22,239,505 2,349,957 1,889,412 48,044,844 18,324,799 1.98 × 108 1.28 × 108
std 52,438.1 879,404 2678,190 26,103,571 55,567.61 467,088.6 7,003,567 433,187.8 318,048.5 9,787,189 4,155,256 13,395,124 674,274.6
median 999,320.4 2,257,125 15,524,785 1.34 × 108 1,074,517 2,970,325 15,115,238 1,549,403 1,649,430 32,645,460 16,778,129 1.81 × 108 1.26 × 108
rank 1 5 9 12 2 6 7 4 3 10 8 13 11
C11-F19 mean 955,907 3,058,450 14,619,890 1.54 × 108 943,673 2,198,561 9,996,685 1,012,821 1,152,320 32,955,731 15,021,597 1.71 × 108 1.27 × 108
best 946,161.6 1,019,342 12,702,812 1.34 × 108 939,631 1,982,053 7,065,299 967,576.5 1,006,006 28,464,019 8,991,833 1.42 × 108 1.25 × 108
worst 965,274.1 8,406,301 16,683,672 1.83 × 108 945,155.6 2,462,708 16,377,179 1,042,643 1,410,250 38,222,795 20,803,805 1.98 × 108 1.29 × 108
std 7877.253 3,580,771 1,652,290 20,568,980 2698.357 216,671.7 4,296,432 32,544.64 184,022.2 4361,221 5,235,721 26,365,907 21,75,679
median 956,096.1 1,404,078 14,546,539 1.49 × 108 944,952.7 2,174,742 8,272,131 1,020,533 1,096,512 32,568,056 15,145,374 1.73 × 108 1.27 × 108
rank 2 6 8 12 1 5 7 3 4 10 9 13 11
C11-F20 mean 9.891135 18.43484 37.38995 91.01355 10.6478 33.26948 50.31143 30.14097 31.4193 106.5034 42.42906 99.89802 120.8118
best 8.48708 17.10456 35.08192 66.45898 9.075328 27.26106 37.94496 24.44492 20.005 96.68012 36.61611 94.66104 117.9591
worst 12.17501 20.77307 38.49468 115.651 12.96167 40.06704 54.83165 34.77377 39.31062 119.9895 48.12816 104.208 122.6439
std 1.597904 1.636928 1.602459 21.7381 1.659265 5.379866 8.261372 4.569823 8.429287 10.42733 5.629644 4.140173 2.131154
median 9.451225 17.93087 37.9916 90.97211 10.27711 32.87492 54.23456 30.67259 33.18078 104.672 42.48599 100.3615 121.3222
rank 1 3 7 10 2 6 9 4 5 12 8 11 13
C11-F21 mean 15.56392 27.48089 47.41507 74.30445 16.73979 34.48503 50.05503 27.46992 27.25074 97.52848 77.12081 96.64377 90.22154
best 11.96234 25.26953 41.00099 52.03457 12.7765 27.49964 44.78979 20.42011 24.60761 88.33535 63.26603 83.14479 55.52377
worst 19.37189 32.64845 56.32061 85.38791 20.57706 46.01433 59.96269 34.30754 30.17099 110.6057 103.444 115.6542 116.5376
std 3.098876 3.475444 7.085416 15.10545 3.240004 8.054631 7.08343 6.257589 2.843483 10.47165 17.91987 13.69907 26.29488
median 15.46073 26.00279 46.16933 79.89766 16.8028 32.21307 47.73381 27.57601 27.11219 95.58645 70.8866 93.88804 94.41237
rank 1 5 7 9 2 6 8 4 3 13 10 12 11
C11-F22 mean 3.703267 15.02557 25.74562 26.00412 4.069952 17.52275 21.89831 13.4942 15.568 20.13739 25.86975 21.49811 25.49193
best 2.68 × 10−10 11.75673 24.83901 25.15683 2.85 × 10−10 8.510385 17.24132 6.548961 10.72236 17.39148 24.1914 17.49104 24.75272
worst 14.81307 19.29177 26.94225 27.78769 16.27981 21.63138 24.82611 16.5131 22.07106 22.56158 27.76547 25.58579 26.07053
std 7.406534 3.129599 1.051112 1.209479 8.139905 6.077377 3.257521 4.67819 5.389997 2.179018 1.524199 3.753819 0.558841
median 1.37 × 10−9 14.52688 25.60061 25.53597 1.48 × 10−9 19.97462 22.7629 15.45736 14.7393 20.29825 25.76107 21.45781 25.57223
rank 1 4 11 13 2 6 9 3 5 7 12 8 10
Sum rank 38 91 161 226 48 140 154 96 91 205 166 189 213
Mean rank 1.809524 4.333333 7.666667 10.7619 2.285714 6.666667 7.333333 4.571429 4.333333 9.761905 7.904762 9 10.14286
Total rank 1 3 7 12 2 5 6 4 3 10 8 9 11
Wilcoxon: p-value 1.81 × 10−7 1.09 × 10−14 1.71 × 10−15 0.522069 8.49 × 10−15 2.42 × 10−14 6.09 × 10−10 2.71 × 10−12 5.56 × 10−15 7.92 × 10−15 8.57 × 10−14 7.92 × 10−15

The simulation results imply that the proposed SOA approach is the best optimizer for handling functions C11-F1, C11-F2, C11-F4 to C11-F6, C11-F8 to C11-F10, F12, F15, F18, and C11-F20 to C11-F22. A comparison of the simulation results indicates that the proposed SOA approach has an acceptable efficiency in dealing with real-world optimization problems against competitor algorithms. Additionally, the results of employing the Wilcoxon rank sum test on the performance of SOA and competitor algorithms on the CEC 2011 test suite show the statistically significant superiority of SOA in competition with the compared algorithms. The performance of SOA and competitor algorithms in dealing with the CEC 2011 test suite is plotted as a boxplot diagram in Figure 7.

Figure 7.

Figure 7

Boxplot diagram of SOA and competitor algorithms performances on the CEC 2011 test suite.

5.2. The SOA Testing on Engineering Optimization Problems

In this subsection, the performance of SOA in solving four engineering design problems from real-world applications is evaluated.

5.2.1. Pressure Vessel Design Problem

The pressure vessel design is a real-world challenge in engineering studies where the goal is to minimize the design cost. The schematic of this design is provided in Figure 8.

Figure 8.

Figure 8

Schematic of the pressure vessel design.

The mathematical model of pressure vessel design problem is as follows [58]:

Consider: X=[x1, x2, x3, x4]=[Ts, Th, R, L].

Minimize: f(x)=0.6224x1x3x4+1.778x2x32+3.1661x12x4+19.84x12x3.

Subject to:

g1(x)=x1+0.0193x3  0, g2(x)=x2+0.00954x3 0,g3(x)=πx32x443πx33+1296000 0, g4(x)=x4240  0.

With

0x1,x2100 and 10x3,x4200.

The optimization results of pressure vessel design using SOA and competitor algorithms are released in Table 9 and Table 10.

Table 9.

Performance of optimization algorithms on the pressure vessel design problem.

Algorithm Optimum Variables Optimum Cost
Ts Th R L
SOA 0.778027 0.384579 40.31228 200 5882.901
WSO 0.778027 0.384579 40.31228 200 5882.901
AVOA 0.778027 0.384579 40.31228 200 5882.901
RSA 0.873804 0.743654 41.80167 200 7974.077
MPA 0.778027 0.384579 40.31228 200 5882.901
TSA 0.780589 0.390787 40.34795 200 5925.31
WOA 0.956571 0.48327 49.13929 105.2553 6351.3
MVO 0.860496 0.426361 44.58435 148.0464 6044.069
GWO 0.779811 0.38726 40.39606 198.8451 5892.513
TLBO 1.997346 0.976593 75.72573 77.86602 24,264.99
GSA 1.129784 0.558452 58.53792 108.2202 9777.026
PSO 1.381856 0.696892 60.63946 169.9479 16,744.76
GA 0.962225 2.050866 47.54579 183.9335 14,893.63
Table 10.

Statistical results of optimization algorithms on pressure vessel design problem.

Algorithm Mean Best Worst Std Median Rank
SOA 5882.901 5882.901 5882.901 1.87 × 10−12 5882.901 1
WSO 5906.961 5882.901 6118.936 58.51093 5882.901 3
AVOA 6318.02 5883.453 7029.777 356.8045 6324.189 6
RSA 12,261.31 7974.077 20,310.05 3514.19 11,063.85 9
MPA 5889.237 5883.856 5893.836 2.708182 5888.898 2
TSA 6257.625 5925.31 7013.933 368.492 6102.727 5
WOA 7683.151 6351.3 11,250.02 1293.839 7295.016 8
MVO 6668.44 6044.069 7322.993 415.1949 6676.802 7
GWO 6112.193 5892.513 7112.804 416.0391 5909.954 4
TLBO 42,144.27 24,264.99 83,025.09 16,815.72 38,698.07 12
GSA 21,921.33 9777.026 35,302.66 7701.707 21,288.72 10
PSO 42,957.13 16,744.76 75,536.88 15,181.17 46,304.65 13
GA 40,300.82 14,893.63 98,448.02 18,294.20 35,672.07 11

Based on the simulation results, the proposed SOA approach has provided the optimal solution with the values of the design variables equal to (0.778027, 0.384579, 40.31228, 200), and the value of the objective function equals to 5882.901. The analysis of the results shows that compared to competitor algorithms. Therefore, SOA has provided better performance in dealing with pressure vessel design. The convergence curve of SOA in achieving the solution for the pressure vessel design problem is drawn in Figure 9.

Figure 9.

Figure 9

SOA’s performance convergence curve on the pressure vessel design.

5.2.2. Speed Reducer Design Problem

The speed reducer design is an engineering subject aiming to minimize the speed reducer’s weight. The schematic of this design is provided in Figure 10.

Figure 10.

Figure 10

Schematic of speed reducer design.

The mathematical model of the speed reducer design problem is as follows [59,60]:

Consider: X=[x1, x2, x3, x4, x5 ,x6 ,x7]=[b, m, p, l1, l2, d1, d2].

Minimize: f(x)=0.7854x1x22(3.3333x32+14.9334x343.0934)1.508x1(x62+x72)+7.4777(x63+x73)+0.7854(x4x62+x5x72).

Subject to:

g1(x)=27x1x22x31  0, g2(x)=397.5x1x22x31 0,g3(x)=1.93x43x2x3x641 0, g4(x)=1.93x53x2x3x741  0,g5(x)=1110x63(745x4x2x3)2+16.9·1061 0,g6(x)=185x73(745x5x2x3)2+157.5·1061  0,g7(x)=x2x3401  0, g8(x)=5x2x11  0,g9(x)=x112x21  0, g10(x)=1.5x6+1.9x41  0,g11(x)=1.1x7+1.9x51  0.

With

2.6x13.6, 0.7x20.8, 17x328, 7.3x48.3, 7.8x58.3, 2.9x63.9, and 5x75.5.

The implementation results of the proposed SOA and competitor algorithms on the speed reducer design problem are released in Table 11 and Table 12.

Table 11.

Performance of optimization algorithms on the speed reducer design problem.

Algorithm Optimum Variables Optimum Cost
b M p b1 b2 d1 d2
SOA 3.5 0.7 17 7.3 7.8 3.350215 5.286683 2996.348
WSO 3.5 0.7 17 7.300003 7.800006 3.350215 5.286683 2996.349
AVOA 3.5 0.7 17 7.3 7.8 3.350215 5.286683 2996.348
RSA 3.6 0.7 17 7.3 8.3 3.351345 5.5 3188.612
MPA 3.5 0.7 17 7.3 7.8 3.350215 5.286683 2996.348
TSA 3.502004 0.7 17 7.531361 7.918844 3.353967 5.292829 3006.665
WOA 3.524215 0.700895 17 7.859427 7.957261 3.351278 5.317321 3038.216
MVO 3.503185 0.7 17 7.425817 7.839415 3.374115 5.286934 3005.882
GWO 3.500789 0.7 17 7.468265 7.818522 3.351642 5.286764 2998.965
TLBO 3.575075 0.710376 26.87747 7.412554 7.933867 3.401006 5.308059 5360.781
GSA 3.555741 0.701286 17.26289 8.153121 8.159038 3.443303 5.348242 3150.666
PSO 3.577873 0.703145 17.69495 7.75669 8.048995 3.736336 5.2889 3289.236
GA 3.57042 0.700615 20.37875 8.029033 8.055597 3.433943 5.362534 3758.934
Table 12.

Statistical results of optimization algorithms on the speed reducer design problem.

Algorithm Mean Best Worst Std Median Rank
SOA 2996.348 2996.348 2996.348 9.33 × 10−13 2996.348 1
WSO 2996.845 2996.349 3004.806 1.876691 2996.367 2
AVOA 3000.507 2996.348 3010.109 4.665488 2999.125 4
RSA 3273.628 3188.612 3363.873 60.87604 3258.238 8
MPA 2999.118 2996.44 3002.078 1.841197 2999.338 3
TSA 3038.484 3006.665 3059.817 14.5261 3039.687 7
WOA 3354.082 3038.216 5582.461 653.6465 3113.028 9
MVO 3032.462 3005.882 3058.964 16.87454 3032.846 6
GWO 3004.446 2998.965 3009.552 3.542339 3004.059 5
TLBO 6.67 × 1013 5360.781 2.32 × 1014 7.04 × 1013 4.58 × 1013 12
GSA 3498.023 3150.666 4508.259 317.1042 3414.037 10
PSO 1.32 × 1014 3289.236 1.32 × 1015 2.95 × 1014 4.5 × 1013 13
GA 6.44 × 1013 3758.934 5.09 × 1014 1.34 × 1014 1.05 × 1013 11

Based on the simulation results, the proposed SOA approach has provided the optimal solution with the values of the design variables equal to (3.5, 0.7, 17, 7.3, 7.8, 3.350215, 5.286683) and the objective function equal to 2996.348. Analysis of the results shows that SOA has provided better performance in handling speed reducer design compared to competitor algorithms. The convergence curve of SOA while solving the speed reducer design problem is drawn in Figure 11.

Figure 11.

Figure 11

SOA’s performance convergence curve on the speed reducer design.

5.2.3. Welded Beam Design

The welded beam design is a real-world application with the aim of minimizing the fabrication cost of the welded beam. The schematic of welded beam design problem is provided in Figure 12.

Figure 12.

Figure 12

Schematic of the welded beam design.

The mathematical model of welded beam design problem is as follows [23]:

Consider: X=[x1, x2, x3, x4]=[h, l, t, b].

Minimize: f(x)=1.10471x12x2+0.04811x3x4 (14.0+x2).

Subject to:

g1(x)=τ(x)13600  0, g2(x)=σ(x)30000  0,g3(x)=x1x4 0, g4(x)=0.10471x12+0.04811x3x4 (14+x2)5.0  0,g5(x)=0.125x1 0, g6(x)=δ (x)0.25  0,g7(x)=6000pc (x) 0.

Here

τ(x)=(τ)2+(2ττ)x22R+(τ)2 , τ=60002x1x2, τ=MRJ,M=6000(14+x22), R=x224+(x1+x32)2,J=2{x1x22[x2212+(x1+x32)2]} , σ(x)=504000x4x32,

δ (x)=65856000(30·106)x4x33 , pc (x)=4.013(30·106)x32x4636196(1x32830·1064(12·106)).

With

0.1x1, x42 and 0.1x2, x310.

The results of using the SOA and competing algorithms on the problem of welded beam design are released in Table 13 and Table 14.

Table 13.

Performance of optimization algorithms on the welded beam design problem.

Algorithm Optimum Variables Optimum Cost
h l t b
SOA 0.20573 3.470489 9.036624 0.20573 1.724852
WSO 0.20573 3.470489 9.036624 0.20573 1.724852
AVOA 0.20573 3.470489 9.036624 0.20573 1.724852
RSA 0.150134 4.75063 10 0.206313 1.979431
MPA 0.20573 3.470489 9.036624 0.20573 1.724852
TSA 0.201353 3.584929 9.045002 0.205782 1.735242
WOA 0.20488 3.546188 8.921686 0.211065 1.754013
MVO 0.203146 3.539276 9.03661 0.205819 1.730769
GWO 0.205462 3.479 9.036729 0.205759 1.72583
TLBO 0.236531 7.25166 7.68074 0.29846 2.791973
GSA 0.192398 4.185734 9.345858 0.219364 1.964869
PSO 0.240686 4.095809 7.000139 0.598026 3.90663
GA 0.133949 6.613311 9.470163 0.396197 3.852019
Table 14.

Statistical results of optimization algorithms on the welded beam design problem.

Algorithm Mean Best Worst std Median Rank
SOA 1.724852 1.724852 1.724852 6.83 × 10−16 1.724852 1
WSO 1.724852 1.724852 1.724854 4.32 × 10−7 1.724852 2
AVOA 1.759209 1.725117 1.892483 0.041877 1.74656 7
RSA 2.279139 1.979431 2.751124 0.211874 2.258755 8
MPA 1.726515 1.725441 1.728092 0.000972 1.726346 3
TSA 1.746863 1.735242 1.761533 0.006875 1.746978 5
WOA 2.509499 1.754013 4.629688 0.875301 2.11047 10
MVO 1.749039 1.730769 1.807243 0.017414 1.745069 6
GWO 1.727289 1.72583 1.730001 0.001078 1.727085 4
TLBO 4.32 × 1013 2.791973 4.69 × 1014 1.24 × 1014 5.331066 12
GSA 2.455232 1.964869 2.876107 0.258565 2.391602 9
PSO 7.27 × 1013 3.90663 3.02 × 1014 1.16 × 1014 5.09 × 1012 13
GA 3.15 × 1013 3.852019 2.37 × 1014 7.65 × 1013 5.36045 11

Based on the simulation results, the proposed SOA approach has provided the optimal solution with the values of the design variables equal to (0.20573, 3.470489, 9.036624, 0.20573) and the objective function equal to 1.724852. Based on the statistical indicators, it is clear that SOA has provided a more effective capability in handling the welded beam design problem compared to competitor algorithms. The SOA con-vergence curve during welded beam design optimization is drawn in Figure 13.

Figure 13.

Figure 13

SOA’s performance convergence curve on the welded beam design.

5.2.4. Tension/Compression Spring Design

The tension/compression spring design is a real-world issue with the goal of minimizing the weight of tension/compression spring. The schematic of this design is provided in Figure 14.

Figure 14.

Figure 14

Schematic of the tension/compression spring design.

The mathematical model of tension/compression spring design problem is as follows [23]:

Consider: X=[x1, x2, x3 ]=[d, D, P].

Minimize: f(x)=(x3+2)x2x12.

Subject to:

g1(x)=1x23x371785x14  0, g2(x)=4x22x1x212566(x2x13)+15108x121 0,

g3(x)=1140.45x1x22x3 0, g4(x)=x1+x21.51  0.

With

0.05x12, 0.25x21.3 and 2 x315.

The simulation results of the tension/compression spring design problem using the SOA and competitor algorithms are released in Table 15 and Table 16.

Table 15.

Performance of optimization algorithms on the tension/compression spring design problem.

Algorithm Optimum Variables Optimum Cost
d D P
SOA 0.051689 0.356718 11.28897 0.012665
WSO 0.051689 0.356716 11.28906 0.012665
AVOA 0.051689 0.356718 11.28897 0.012665
RSA 0.05 0.310493 15 0.013196
MPA 0.051688 0.356703 11.28982 0.012665
TSA 0.051504 0.352152 11.57771 0.012683
WOA 0.052121 0.36721 10.69936 0.012669
MVO 0.061321 0.635221 3.976356 0.014275
GWO 0.05171 0.357118 11.27238 0.012674
TLBO 0.069275 0.939724 2 0.018039
GSA 0.05514 0.439926 8.921418 0.014608
PSO 0.068994 0.933432 2 0.017773
GA 0.069308 0.940961 2 0.01808
Table 16.

Statistical results of optimization algorithms on the tension/compression spring design problem.

Algorithm Mean Best Worst Std Median Rank
SOA 0.012665 0.012665 0.012665 1.19 × 10−18 0.012665 1
WSO 0.012683 0.012665 0.012851 4.4 × 10−5 0.012666 3
AVOA 0.013316 0.012684 0.014868 0.000655 0.013049 7
RSA 0.026737 0.013196 0.152646 0.033029 0.013333 11
MPA 0.012676 0.012666 0.01269 7.04 × 10−6 0.012674 2
TSA 0.012967 0.012683 0.013663 0.00028 0.012883 5
WOA 0.013266 0.012669 0.01558 0.000739 0.013041 6
MVO 0.017716 0.014275 0.018434 0.000985 0.017988 8
GWO 0.012769 0.012674 0.013195 0.00012 0.012727 4
TLBO 0.018633 0.018039 0.019221 0.000332 0.018711 9
GSA 0.019185 0.014608 0.036067 0.004735 0.017658 10
PSO 1.99 × 1013 0.017773 3.97 × 1014 8.88 × 1013 0.017773 13
GA 3.38 × 1012 0.01808 5.31 × 1013 1.19 × 1013 0.026219 12

Based on the simulation results, the proposed SOA approach has provided the optimal solution with the values of the design variables equal to (0.051689, 0.356718, 11.28897) and the objective function equal to 0.012665. Comparing the obtained results indicates the superiority of SOA in dealing with the tension/compression spring design problem compared to competing algorithms. The SOA convergence curve while achieving the optimal design for the tension/compression spring design problem is drawn in Figure 15.

Figure 15.

Figure 15

SOA’s performance convergence curve on the tension/compression spring.

6. Conclusions and Future Works

This paper introduced a new swarm-based metaheuristic algorithm named the Serval Optimization Algorithm (SOA) based on the simulation of serval behaviors in nature. The serval strategy during hunting in the three stages of prey selection, attack, and the chase is the fundamental inspiration of SOA. Different steps of SOA were stated and mathematically modeled in two phases of exploration and exploitation. The effectiveness of SOA in solving optimization problems was tested on thirty-nine benchmark functions from the CEC 2017 test suite and the CEC 2019 test suite. The SOA’s results were compared with the performance of the other twelve well-known metaheuristic algorithms. The optimization results showed that SOA had performed better by balancing exploration and exploitation and had superior performance compared to competitor algorithms. Employing the proposed approach in optimizing the CEC 2011 test suite and four engineering design challenges demonstrated SOA’s evident ability to address real-world applications.

The introduction of SOA enables several research tasks for future studies. Designing the multi-objective version of SOA and using it in multi-objective optimization problems, developing the binary version of SOA, and using it in applications that require binary algorithms, such as feature selection, are among the most special suggestions for future studies. The use of SOA in various optimization problems in science and real-world applications are among the other recommendations of this article for future research.

Acknowledgments

The authors thank University of Hradec Králové for support.

Author Contributions

Conceptualization, P.T.; methodology, P.T.; software, M.D.; validation, P.T. and M.D.; formal analysis, M.D.; investigation, P.T.; resources, P.T.; data curation, P.T. and M.D.; writing—original draft preparation, P.T. and M.D.; writing—review and editing, P.T. and M.D.; visualization, P.T.; supervision, P.T.; project administration, M.D.; funding acquisition, P.T. All authors have read and agreed to the published version of the manuscript.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Not applicable.

Conflicts of Interest

The authors declare no conflict of interest.

Funding Statement

This research was funded by Project of Excellence Faculty of Science, University of Hradec Králové, grant number 2210/2022.

Footnotes

Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

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