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Erschienen in:
2009 | OriginalPaper | Buchkapitel
Multi-swarm Particle Swarm Optimizer with Cauchy Mutation for Dynamic Optimization Problems
verfasst von : Chengyu Hu, Xiangning Wu, Yongji Wang, Fuqiang Xie
Erschienen in: Advances in Computation and Intelligence
Verlag: Springer Berlin Heidelberg
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Many real-world problems are dynamic, requiring an optimization algorithm which is able to continuously track a changing optimum over time. This paper presents a new variant of Particle Swarm Optimization (PSO) specifically designed to work well in dynamic environments. The main idea is to divide the population of particles into a set of interacting swarms. These swarms interact locally by dynamic regrouping and dispersing. Cauchy mutation is applied to the global best particle when the swarm detects the environment of the change. The dynamic function (proposed by Morrison and De Jong) is used to test the performance of the proposed algorithm. The comparison of the numerical experimental results with those of other variant PSO illustrates that the proposed algorithm is an excellent alternative to track dynamically changing optima.