关键词: 随机微粒群算法 遗传算法 轮盘赌选择 全局优化

Abstract:

Based on the stochastic particle swarm optimization algorithm that guarantees global convergence, an improved stochastic particle swarm optimization algorithm named GAR-SPSO is proposed. During the evolution of SPSO, the optimal particles produced by the genetic algorithm of roulette wheel selection s ubstitute for the stopping particles, and take part in the evolution of the next generation. Through the experiments of five multi-modal test functions,the result of simulation proves that the speed of convergence and the rate of convergence for GAR-SPSO are better than SPSO in case of the same dimension of the search space.

Key words: stochastic particle swarm optimization, genetic algorithm, roulette wheel selection, global optimization