Utilize este identificador para referenciar este registo: http://hdl.handle.net/10400.22/3186
Título: Entropy diversity in multi-objective particle swarm optimization
Autor: Pires, E. J. Solteiro
Machado, J. A. Tenreiro
Oliveira, P. B. Moura
Palavras-chave: Multi-objective particle swarm optimization
Shannon entropy
Diversity
Data: 2013
Editora: MDPI AG
Relatório da Série N.º: Entropy; Vol. 15, Issue 12
Resumo: Multi-objective particle swarm optimization (MOPSO) is a search algorithm based on social behavior. Most of the existing multi-objective particle swarm optimization schemes are based on Pareto optimality and aim to obtain a representative non-dominated Pareto front for a given problem. Several approaches have been proposed to study the convergence and performance of the algorithm, particularly by accessing the final results. In the present paper, a different approach is proposed, by using Shannon entropy to analyzethe MOPSO dynamics along the algorithm execution. The results indicate that Shannon entropy can be used as an indicator of diversity and convergence for MOPSO problems.
Peer review: yes
URI: http://hdl.handle.net/10400.22/3186
ISSN: 1099-4300
Versão do Editor: http://www.mdpi.com/1099-4300/15/12/5475
Aparece nas colecções:ISEP – GECAD – Artigos

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