标题：Empirical Analysis of Effect of Particle Swarm Optimization Inertia Weight Strategies over Particle Swarm Optimization with Aging Leader and Challengers
期刊名称：International Journal of Hybrid Information Technology
印刷版ISSN：1738-9968
出版年度：2015
卷号：8
期号：11
页码：375-388
DOI：10.14257/ijhit.2015.8.11.33
出版社：SERSC
摘要：Particle swarm optimization is the optimization technique motivated by swarm intelligence and aims to find the best solution in the swarm. Aging leader and challengers with Particle swarm optimization (ALC-PSO) is a population based optimization method which introduced the concept of aging and challenger generation in the PSO technique. This variant of PSO has been successful in preventing premature convergence of PSO and maintaining swarm diversity. In this paper, we briefly reviewed the inertia weight parameter and its strategies in PSO and experimentally analyzed the effect of inertia weight strategies on ALC-PSO performance. Comparison is drawn between PSO and ALC-PSO based on these strategies. Results are obtained using five different benchmark functions.
关键词：Aging; leader; particle swarm optimization; convergence; population
