Utilize este identificador para referenciar este registo:
https://hdl.handle.net/1822/37046
Título: | DDMOA: Descent Directions based Multiobjective Algorithm |
Autor(es): | Denysiuk, Roman Costa, L. Espírito Santo, I. A. C. P. |
Palavras-chave: | Multiobjective optimization Evolutionary algorithms Pattern search Performance assessment |
Data: | 2012 |
Resumo(s): | Hybridization of local search based algorithms with evolutionary algorithms is still an under-explored research area in multiobjective optimization. In this paper, we propose a new multiobjective algorithm based on a local search method. The main idea is to generate new non-dominated solutions by adding to a parent solution a linear combination of descent directions of the objective functions. Additionally, a strategy based on subpopulations is implemented to avoid the direct computation of descent directions for the entire population. The evaluation of the proposed algorithm is performed on a set of benchmark test problems allowing a comparison with the most representative stateof- the-art multiobjective algorithms. The results show that the proposed approach is highly competitive in terms of the quality of non-dominated solutions, robustness and the computational efficiency. |
Tipo: | Artigo em ata de conferência |
URI: | https://hdl.handle.net/1822/37046 |
Arbitragem científica: | yes |
Acesso: | Acesso restrito UMinho |
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Ficheiros deste registo:
Ficheiro | Descrição | Tamanho | Formato | |
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d29.pdf Acesso restrito! | 164,04 kB | Adobe PDF | Ver/Abrir |