| Abstrakt: |
To solve the constrained optimization problem, a new algorithm WDFSO is obtained by combining the exterior penalty function method and an improved snake optimization algorithm. Firstly, the constrained optimization problem is transformed into a series of bound-constrained optimization problems by the exterior penalty function method. Then, the improved snake optimization algorithm based on the oppositional learning of the centroid variation strategy and the population classification strategy is used to solve the bound-constrained optimization problem, and obtain the solution of the constrained optimization problem. In order to verify the effectiveness of WDFSO algorithm, 19 benchmark constrained optimization problems in CEC2006 are selected for numerical experiments, and the Wilcoxon rank sum test is used to prove the algorithm significance. The experimental results show that WDFSO algorithm has higher convergence accuracy and better stability than the comparison algorithms. Finally, WDFSO algorithm is applied to solve two engineering constraint optimization problems, and the results show that WDFSO algorithm has better performance. [ABSTRACT FROM AUTHOR] |
