Utilize este identificador para referenciar este registo:
https://hdl.handle.net/1822/21012
Título: | A new hybrid evolutionary multiobjective algorithm guided by descent directions |
Autor(es): | Denysiuk, Roman Costa, L. Espírito Santo, I. A. C. P. |
Palavras-chave: | Multiobjective optimization Evolutionary algorithms Pattern search Performance assessment |
Data: | 2013 |
Editora: | Springer |
Revista: | Journal of Mathematical Modelling and Algorithms |
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 a linear combination of descent directions of the objective functions to a parent solution. 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 state-of-the-art multiobjective algorithms. The results show that the proposed approach is highly competitive in terms of the quality of non-dominated solutions and robustness. |
Tipo: | Artigo |
URI: | https://hdl.handle.net/1822/21012 |
DOI: | 10.1007/s10852-012-9208-2 |
ISSN: | 1570-1166 |
Versão da editora: | http://dx.doi.org/10.1007/s10852-012-9208-2 |
Arbitragem científica: | yes |
Acesso: | Acesso restrito UMinho |
Aparece nas coleções: | CAlg - Artigos em revistas internacionais / Papers in international journals |
Ficheiros deste registo:
Ficheiro | Descrição | Tamanho | Formato | |
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ddmoa.pdf Acesso restrito! | 4,14 MB | Adobe PDF | Ver/Abrir |