期刊名称：International Journal of Advanced Research in Computer Engineering & Technology (IJARCET)
印刷版ISSN：2278-1323
出版年度：2012
卷号：1
期号：10
页码：265-267
出版社：Shri Pannalal Research Institute of Technolgy
摘要：Particle Swarm Optimization (PSO) is a stochastic global optimization method which is originated from the reproduction of the social performance of birds within a flock. Differential Evolution (DE)is a method that optimizes a problem by iteratively trying to improve an applicant solution with regard to a given determine or feature. The main purpose of this cram work is to nearby the major techniques for quickly verdict the global solution. In this paper combination of PSO and DE is proposed for quickly finding the global solutions. The multibenchmark, multimodal functions are used to test the performance of the proposed methods. The expected will be less time taken as compare to other algorithm.
