关键词: 差分进化, 动态调整, 并行, 变异策略

Abstract: A novel parallel differential evolution (NPDE) algorithm with dynamically adjusting the number of subpopulation individuals was proposed for solving complex optimization problems. In the NPDE algorithm, the initial population was divided into three subpopulations based on the fitness values of individuals, which were employed for global and local search respectively. The number of the subpopulation was dynamically adapted according to the search phases. Different mutation strategies were used to different subpopulation respectively. It coordinated the exploitation ability and the exploration ability of algorithm. Experiments concerning various benchmark functions were designed to test the performance of the NPDE algorithm, and the results show that it can get high performance while dealing with various complex problems.

Key words: Differential Evolution (DE), dynamic adjustment, parallel, mutation strategy