关键词: 约束优化问题, 差分进化算法, 佳点集, 变异策略

Abstract: An improved differential evolution algorithm is proposed to solve constrained optimization problems, which does not introduce penalty parameters to deal with constraints. In the process of evolution, the individuals generation based on good-point-set method is introduced into the evolutionary algorithm initial step. In order to improve global convergence and convergence speed of the proposed algorithm, DE/best/1 mutation scheme and DE/rand/1 mutation scheme are used to the feasible solution and the infeasible solution respectively. Several class Benchmark problems are tested, the results show that the proposed algorithm is an effective way for constrained optimization problems.

Key words: constrained optimization problems, Differential Evolution（DE） algorithm, good point set, mutation strategy