Particle Swarm Optimization Algorithm Based on Velocity DifferentialMutation

摘要：

To deal with the problem of premature local convergence, slow search speed and low convergence accuracy in the late evolutionary, this paper proposes a particle swarm optimization algorithm based on velocity differential mutation (VDMPSO).Firstly, The cause of local convergence in the basic PSO algorithm is elaborated. Secondly, strategies of direct mutation for the particle velocity rather than the traditional particle position with differential evolution algorithm based on analying the relations of the particle velocity and the population diversity is introduced to improve the ability of effectively breaking away from the local optimum. By adding the mutation operation to the basic PSO algorithm, the proposed algorithm can maintain the characteristic of fast speed. Finally, the signficant performances in quality of the optimal solutions, the global search ability and convergence speed of algorithm proposed in this paper are validated by optimizing four benchmark functions.

关键词： Particle Swarm Optimization Differential Evolution Velocity Mutation Global Optimization

作者: Shanhe Jiang Qishen Wang Julang Jiang

作者单位: Department of Physics and Power Engineering, Anqing Normal College, Anqing 246011,China

会议类型: 国际会议

会议名称: 2009年中国控制与决策会议(2009 Chinese Control and Decision Conference)

会议地点: 广西桂林

会议语种:英文

页码: 1860-1865

在线出版日期: 2009-06-17（万方平台首次上网日期，不代表论文的发表时间）