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Publication Details
AFRICAN RESEARCH NEXUS
SHINING A SPOTLIGHT ON AFRICAN RESEARCH
mathematics
Locating multiple optima using particle swarm optimization
Applied Mathematics and Computation, Volume 189, No. 2, Year 2007
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Description
Many scientific and engineering applications require optimization methods to find more than one solution to multi-modal 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. © 2007 Elsevier Inc. All rights reserved.
Authors & Co-Authors
Brits, R.
South Africa, Pretoria
University of Pretoria
Engelbrecht, Andries Petrus
South Africa, Pretoria
University of Pretoria
van den Bergh, Frans
South Africa, Pretoria
The Council for Scientific and Industrial Research
Statistics
Citations: 238
Authors: 3
Affiliations: 2
Identifiers
Doi:
10.1016/j.amc.2006.12.066
ISSN:
00963003
Research Areas
Genetics And Genomics
Study Design
Cross Sectional Study