期刊名称：International Journal of Advances in Soft Computing and Its Applications
印刷版ISSN：2074-8523
出版年度：2010
卷号：2
期号：1
出版社：International Center for Scientific Research and Studies
摘要：Annealing (SA). Particle Swarm Optimization is Swarm Intelligence based algorithm to find a solution to an optimization problem in search space. SA is a generic probabilistic metaheuristic for locating the global minimum of a given function in a large search space. In standard PSO the non-oscillatory route can quickly cause a particle to stagnate and also it may prematurely converge on suboptimal solutions that are not even guaranteed to local optimal solution. The proposed system improves the solution by incorporating the working principles of SA to Standard PSO to diversify the particle position. Experiment results are examined with benchmark functions. It demonstrates that the proposed PSO outperforms the standard PSO
关键词：Convergence; Global Minimum; PSO; Simulated Annealing; ;Stagnation
