Optimization of the Particle Swarm Algorithm

摘要：

　　Particle Swarm Optimization is a swarm intelligence based and stochastic algorithm to solve the optimization problem.This paper presents the Multidimensional Particle Swarm algorithm with non-equidistant discrete input data such as E-Series or Renard numbers for circuit design.The authors describe the optimization of this method for different circuit designs,agent recycling,and omission of already computed points.The problem of omission of already computed points is to determinate when it is faster to omit the points than compute them.The personal omission history can be used for agent recycling or trajectory corrections.There is also described effect of recycled agents with corrected parameters on the convergence of optimalization.Parameters corrections are based on the principles of genetic algorithms in the other words inheritance from the best rated agents.System of agents rating is described briefly.

作者: J.Chytil

作者单位: Department of Theoretical and Experimental Electrical Engineering Brno University of Technology,Technicka 12,Brno 616 00,Czech Republic

会议类型: 国际会议

会议名称: Progress in Electromagnetics Research Symposium 2014(2014年电磁学研究新进展学术研讨会)

会议地点: 广州

会议语种:英文

页码: 2355-2359

在线出版日期: 2014-08-01（万方平台首次上网日期，不代表论文的发表时间）