Publicação
A new algorithm to identify all global maximizers based on simulated annealing
| Resumo: | In this work we consider the problem of finding all the global maximizers of a given nonlinear optimization problem. We propose a new algorithm that combines the simulated annealing (SA) method with a function stretching technique, to generate a sequence of global maximization problems that are defined whenever a new maximizer is identified. To find the global maximizers, we apply the SA algorithm to the sequence of maximization problems. Results of numerical experiments with a set of well-known test problems show that the proposed method is effective. We also compare the performance of our algorithm with other multi-global optimizers. |
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| Autores principais: | Pereira, Ana I. |
| Outros Autores: | Fernandes, Edite M.G.P. |
| Assunto: | Global optimization Simulated annealing Multiglobal optimization |
| Ano: | 2005 |
| País: | Portugal |
| Tipo de documento: | comunicação em conferência |
| Tipo de acesso: | acesso aberto |
| Instituição associada: | Instituto Politécnico de Bragança |
| Idioma: | inglês |
| Origem: | Biblioteca Digital do IPB |
| Resumo: | In this work we consider the problem of finding all the global maximizers of a given nonlinear optimization problem. We propose a new algorithm that combines the simulated annealing (SA) method with a function stretching technique, to generate a sequence of global maximization problems that are defined whenever a new maximizer is identified. To find the global maximizers, we apply the SA algorithm to the sequence of maximization problems. Results of numerical experiments with a set of well-known test problems show that the proposed method is effective. We also compare the performance of our algorithm with other multi-global optimizers. |
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