关键词: 粒子群优化算法, 局部最优, 紧凑度, 调度处理, 寻优精度, 收敛速度

Abstract: To the problems of slow convergence and easy to fall into local optimization appeared in standard particle swarm optimization, this paper proposes a particle compaction and scheduling based particle swarm optimization (PCS-PSO). Firstly, this paper presents the regulations of particles’ compaction and scheduling. In order to avoid particles to stay in local optimization, PCS-PSO evaluates dynamically particle’s compaction and schedules the particle when the value of the particle’s compaction is beyond the threshold. Compared with standard particle swarm optimization and other optimization algorithms using 11 benchmark functions, the experimental results show that PCS-PSO has better behaviors in convergence accuracy and speed.

Key words: particle swarm optimization, local optimization, compaction, scheduling, accuracy of convergence, speed of convergence