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Novel fish swarm heuristics for bound constrained global optimization problems

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Resumo:The heuristics herein presented are modified versions of the artificial fish swarm algorithm for global optimization. The new ideas aim to improve solution accuracy and reduce computational costs, in particular the number of function evaluations. The modifications also focus on special point movements, such as the random, search and the leap movements. A local search is applied to refine promising regions. An extension to bound constrained problems is also presented. To assess the performance of the two proposed heuristics, we use the performance profiles as proposed by Dolan and More in 2002. A comparison with three stochastic methods from the literature is included.
Autores principais:Rocha, Ana Maria A. C.
Outros Autores:Fernandes, Edite Manuela da G. P.; Martins, Tiago F. M. C.
Assunto:Global optimization Derivative-free method Swarm intelligence Heuristics
Ano:2011
País:Portugal
Tipo de documento:comunicação em conferência
Tipo de acesso:acesso aberto
Instituição associada:Universidade do Minho
Idioma:inglês
Origem:RepositóriUM - Universidade do Minho

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