The Study on Dynamic Population Size Improvements for Classical Particle Swarm Optimization

摘要：

In this work we presented two dynamic population size improvements for the classical PSO. EP-PSO started with a small number of particles and increased the number of particles dynamically by iteratively duplicating the updated particles. DP-PSO started with a large number of particles then reduced the number by dropping the worst performing half iteratively. Both EP-PSO and DP-PSO reduced the execution time by 60％ on average compared to the classical PSO. EP-PSO fared quite badly when convergence rate and convergence ability to the global optimum was considered. On the other hand, DPPSO performed reasonably well compared to the classical PSO but at a much faster convergence and execution speed.

关键词： optimization particle swarm optimization dynamic population size

作者: Chen Lei

作者单位: Basic Courses Teaching Department, the Chinese Peoples Armed Police Force Academy

会议类型: 国际会议

会议名称: 2011 International Conference on Computer Science and Network Technology(2011计算机科学与网络技术国际会议 ICCSNT 2011)

会议地点: 哈尔滨

会议语种:英文

页码: 430-433

在线出版日期: 2011-12-24（万方平台首次上网日期，不代表论文的发表时间）