期刊名称：International Journal of Computer Science Issues
印刷版ISSN：1694-0784
电子版ISSN：1694-0814
出版年度：2012
卷号：9
期号：5
出版社：IJCSI Press
摘要：Particle Swarm Optimization is a comparatively recent heuristic technique, introduced by Kenedy and Eberthart in 1995. It is very similar to Genetic Algorithm and it is also a population based method. Many developments have been carried out to the standard Particle Swarm Optimization algorithm. Due to the less computational effort PSOs are very widely being used as an optimization tool. The GA is discrete in nature where as the PSO is inherently continuous. As many variations of the PSO are being popular the motto of this paper is to make analysis of the existing modified versions of standard Particle Swarm Optimization algorithm and to suggest a new variant of PSO. This paper is divided into two parts. The first part is doing analysis of the time variant inertia weight methods suggested by different researchers. In the second part a new method of updating the inertia weight has been proposed. It is also implemented using Mat Lab and proven as worthy than the existing weight updating methods
关键词：Particle Swarm Optimization; Swarm Intelligence; Meta Heuristic Algorithm; Inertia Weight
