关键词: 多种群, 多策略, 并行, 差分进化

Abstract: In order to improve the accuracy and efficiency of parallel differential evolution (DE), this paper proposes a parallel differential evolution with multi-population and multi-strategy, which provides a way to rebustly address various optimization problems. This algorithm divides an initial population into several sub-populations, and then they evolve with different DE strategies. The sub-populations evolve independently at first, and then communicate with each other at regular intervals. By using the proposed multi-population and multi-strategy, the parallel realization of the algorithm can save the computation time while searching with different optimization strategies. The experimental results show that the proposed algorithm is feasible and effective for solving different optimization problems.

Key words: multi-population, multi-strategy, parallel, differential evolution