Dynamic Multi-Swarm Particle Swarm Optimizer with Local Search

descriptionPublicationkeyboard_double_arrow_right Article , Conference object 13 Dec 2005Publisher:IEEEJournal:2005 IEEE Congress on Evolutionary Computation, volume 1, pages 522-528

Authors: Jing J. Liang; Ponnuthurai N. Suganthan;

doi: 10.1109/cec.2005.1554727

Dynamic Multi-Swarm Particle Swarm Optimizer with Local Search

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Abstract

In this paper, the performance of a modified dynamic multi-swarm particle swarm optimizer (DMS-PSO) on the set of benchmark functions provided by CEC2005 is reported. Different from the existing multi-swarm PSOs and local versions of PSO, the swarms are dynamic and the swarms' size is small. The whole population is divided into many small swarms, these swarms are regrouped frequently by using various regrouping schedules and information is exchanged among the swarms. The quasi-Newton method is combined to improve its local search ability

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Nanyang Technological University
Singapore

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