关键词: 粒子群优化, 免疫机制, 动态拓扑, 列维变异

Abstract: Focused on the issue that the Particle Swarm Optimization（PSO） is easy to fall into local optimal and accuracy computation, this paper puts forward a Hybrid PSO Algorithm of Dynamic Topology with Levy mutation（DLPSO）. It introduces dynamic topology Dbest mechanism into the PSO algorithm to adapt particle swarm evolution, the particles are divided into global optimal particle, exploring particles and non target particle based on the solution at each iteration. Levy mutation is introduced in the adaptive mutation of offspring in the immune PSO to ensure the diversity. The DLPSO algorithm is tested by seven benchmark test functions, and the numerical experimental results show that the new algorithm has good convergence efficiency, high accuracy, and good stability.

Key words: particle swarm optimization, immune mechanism, dynamic topology, Levy mutation