关键词: 粒子群优化算法, 竞选领导, 细菌觅食算法, Metropolis准则

Abstract: For the question that standard particle swarm optimization algorithm is easy to fall into local optimal solution, poor in global search ability because of the lost of diversity of particles. This article introduces a new particle swarm optimization algorithm based on campaign leader strategy. It starts the campaign mechanism when the leadership of the global optimal particle loses. It selects a new leader which has more leadership skills to enhance the global search ability of the algorithm after optimizing the elite particles with bacterial foraging algorithm chemotaxis operator. Experimental studies are carried out on four classical functions, and the computational results show?that the algorithm prevents the premature phenomenon effectively and improves the convergence precision without affecting the convergence speed.

Key words: particle swarm optimization, campaign leader, bacterial foraging algorithm, Metropolis criterion