An Innovative Differentiated Creative Search Based on Collaborative Development and Population Evaluation

. 2025 Apr 23;10(5):260. doi: 10.3390/biomimetics10050260

Algorithm 1. Multi Strategy Differentiated Creative Search (MSDCS)

1: Initialization: X_i(i = 1, 2, 3, …, NP), FEs = 0, FEs_max

2: Evaluate the fitness values of the initial population X

3: while (FEs < FEs_max) do

4: Calculate

S c o r e

of each individual using Equation (12)//PES

5: Sort the population in ascending order of

S c o r e

6: for every individual, do

7: Calculate the

η_{i}^{t}

and

ϑ_{i}^{t}

using Equations (2) and (3)

8: Randomly select

j_{r a n d}

using Equation (5)

9: if i == N

10: Update the

v_{N}

using Equation (9)

11: else if

i \leq N_{s}

12: Update the

v_{i, j}

using Equation (8)

13: else

14: Update the

v_{i, j}

using Equation (6)

15: end if

16: Update the Xnew_i using Equation (4)

17: FEs = Fes + 1

18: end for

19: Calculate

μ

and

C

using Equations (14) and (15)//CDM

20: Generate

N_{c}

new individuals using Equation (16)//CDM

21: FEs = Fes + N_c

22: Calculate the Nnew using Equation (13)//LPSR

23: Shrinking X by discarding the worst solutions

24: end while

25: Return best individual