关键词: 粒子群优化算法, 鲶鱼效应, 混沌, 差分进化算法, 混合算法

Abstract: To improve the performance of particle swarm optimization algorithm, the idea of “catfish effect” is introduced to transform the individual evolutionary strategies of particle swarm. Chaos method is used to improve the population search strategy, and the two are put together, not only improving population breadth search ability, but also enhancing the depth of search capability. With the differential evolution algorithm to be mixed, algorithms complement each other, forming a novel hybrid algorithm, better coordinating the contradiction between the breadth search and depth search, and enhancing the performance of the algorithm. After testing the three standard functions, the simulation results show that this algorithm’s capability of escaping from local trap and search accuracy are significantly improved.

Key words: particle swarm optimization algorithm, catfish effect, chaos, differential evolution algorithm, hybrid algorithm