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Please use this identifier to cite or link to this item: http://hdl.handle.net/10204/801

Title: Locating multiple optima using particle swarm optimization
Authors: Brits, R
Engelbrecht, AP
Van den Bergh, F
Keywords: Particle swarm optimization
Multi-modal optimization problems
Issue Date: 2007
Publisher: Elsevier Science Inc
Citation: Brits, R, Engelbrecht, AP and Van den Bergh. 2007. Locating multiple optima using particle swarm optimization. Applied Mathematics and Computation. Vol. 189, pp 1859-1883
Abstract: Many scientific and engineering applications require optimization methods to find more than one solution to multimodal optimization problems. This paper presents a new particle swarm optimization (PSO) technique to locate and refine multiple solutions to such problems. The technique, NichePSO, extends the inherent unimodal nature of the standard PSO approach by growing multiple swarms from an initial particle population. Each subswarm represents a different solution or niche; optimized individually. The outcome of the NichePSO algorithm is a set of particle swarms, each representing a unique solution. Experimental results are provided to show that NichePSO can successfully locate all optima on a small set of test functions. These results are compared with another PSO niching algorithm, lbest PSO, and two genetic algorithm niching approaches. The influence of control parameters is investigated, including the relationship between the swarm size and the number of solutions (niches). An initial scalability study is also done.
Description: http://www.sciencedirect.com/science/journal/00963003
URI: http://hdl.handle.net/10204/801
ISSN: 0096-3003
Appears in Collections:Remote Sensing
General science, engineering & technology

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