An Overview of Particle Swarm Optimization Variants
作者： Muhammad Imran , Rathiah Hashim , Noor Elaiza Abd Khalid
DOI: 10.1016/J.PROENG.2013.02.063
关键词:
摘要: Abstract Particle swarm optimization (PSO) is a stochastic algorithm used for the problems proposed by Kennedy [1] in 1995. It very good technique problems. But still there drawback PSO that it stuck local minima. To improve performance of PSO, researchers different variants PSO. Some try to improving initialization swarm. them introduce new parameters like constriction coefficient and inertia weight. define method weight work on global best particles introducing mutation operators In this paper, we will see with respect initialization, operators.
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