Adaptively choosing neighbourhood bests using species in a particle swarm optimizer for multimodal function optimization

Li, X 2004, 'Adaptively choosing neighbourhood bests using species in a particle swarm optimizer for multimodal function optimization', in K. Deb et al. (ed.) Genetic and Evolutionary Computation - GECCO 2004, Seattle, USA, 1 June 2004, pp. 105-116.


Document type: Conference Paper
Collection: Conference Papers

Title Adaptively choosing neighbourhood bests using species in a particle swarm optimizer for multimodal function optimization
Author(s) Li, X
Year 2004
Conference name Annual Genetic and Evolutionary Computation
Conference location Seattle, USA
Conference dates 1 June 2004
Proceedings title Genetic and Evolutionary Computation - GECCO 2004
Editor(s) K. Deb et al.
Publisher Springer
Place of publication Berlin, Germany
Start page 105
End page 116
Total pages 12
Abstract This paper proposes an improved particle swarm optimizer using the notion of species to determine its neighbourhood best values, for solving multimodal optimization problems. In the proposed speciesbased PSO (SPSO), the swarm population is divided into species subpopulations based on their similarity. Each species is grouped around a dominating particle called the species seed. At each iteration step, species seeds are identified from the entire population and then adopted as neighbourhood bests for these individual species groups separately. Species are formed adaptively at each step based on the feedback obtained from the multimodal fitness landscape. Over successive iterations, species are able to simultaneously optimize towards multiple optima, regardless of if they are global or local optima. Our experiments demonstrated that SPSO is very effective in dealing with multimodal optimization functions with lower dimensions.
Subjects Artificial Intelligence and Image Processing not elsewhere classified
Keyword(s) Adaptive behaviour
Artificial intelligence
Multimodal optimisation
Particle swarm optimisation
Copyright notice © Springer-Verlag Berlin Heidelberg 2004
ISBN 978-3-540-22344-3
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