Surrogate-Assisted Hybrid Meta-Heuristic Algorithm with an Add-Point Strategy for a Wireless Sensor Network

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. 2023 Feb 9;25(2):317. doi: 10.3390/e25020317

Algorithm 5 Pseudo-code for the SAGD algorithm.

Input:
$RunGOA$ = 1; $FES$ = ps + 1; $gen$ = 0; $K$ = 30; $r$ : random values between 0 and 1;
Output:
Optimal solution and its fitness value;
1:
The solution space is initialized by Latin hypercube sampling;
2:
Use the real fitness function to calculate the fitness value for all individuals and the average individual;
3:
while $F E S < F E S m a x$ do
4:
Initialize the population with the first ps samples in the SDB;
5:
if $F E S > p s + 1$ then
6:
Preserving the information of the local surrogate model and constructing the local surrogate model using Algorithm 3;
7:
else
8:
Putting populations and mean individuals and their true fitness values into a database;
9:
end if
10:
while $g e n < K$ do
11:
if $R u n G O A = 1$ then
12:
for $X_{i}$ do
13:
if $r > 0.5$ then
14:
Execution of Equation (7);
15:
else
16:
Execution of Equation (16);
17:
end if
18:
A local RBF surrogate model is used to estimate the fitness values of the evolved individuals and the original individuals, and the individuals with high fitness values are retained;
19:
end for
20:
gen = gen + 1;
21:
else
22:
for $X_{i}$ do
23:
Generation of a mutated individual by Equation (22);
24:
Generation of test individuals by Equation (25);
25:
A local RBF surrogate model is used to estimate the fitness values of the evolved individuals and the original individuals, and the individuals with high fitness values are retained;
26:
end for
27:
gen = gen + 1;
28:
end if
29:
end while
30:
if When the meta-heuristic algorithm updates the location of the population individuals that are all present in the SDB then
31:
then invert the value of RunGOA;
32:
else

Calculating the true fitness value by selecting individuals using the add-point strategy of Algorithm 4 to update the SDB;
33:
if The meta-heuristic algorithm did not find a better solution then
34:
Invert the value of RunGOA;
35:
else
36:
Retain the value of RunGOA;
37:
end if
38:
end if
39:
end while