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Conceptual comparison of population based metaheuristics for engineering problems.
Adekanmbi, Oluwole; Green, Paul.
Afiliação
  • Adekanmbi O; Department of Finance and Information Management, Durban University of Technology, P.O. Box 101112, Scottsville, Pietermaritzburg 3209, South Africa.
  • Green P; Department of Finance and Information Management, Durban University of Technology, P.O. Box 101112, Scottsville, Pietermaritzburg 3209, South Africa.
ScientificWorldJournal ; 2015: 936106, 2015.
Article em En | MEDLINE | ID: mdl-25874265
ABSTRACT
Metaheuristic algorithms are well-known optimization tools which have been employed for solving a wide range of optimization problems. Several extensions of differential evolution have been adopted in solving constrained and nonconstrained multiobjective optimization problems, but in this study, the third version of generalized differential evolution (GDE) is used for solving practical engineering problems. GDE3 metaheuristic modifies the selection process of the basic differential evolution and extends DE/rand/1/bin strategy in solving practical applications. The performance of the metaheuristic is investigated through engineering design optimization problems and the results are reported. The comparison of the numerical results with those of other metaheuristic techniques demonstrates the promising performance of the algorithm as a robust optimization tool for practical purposes.

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2015 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2015 Tipo de documento: Article