A novel multiobjective optimization algorithm based on bacterial chemotaxis
| Contribuinte(s) |
UNIVERSIDADE DE SÃO PAULO |
|---|---|
| Data(s) |
18/10/2012
18/10/2012
2010
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| Resumo |
In this article a novel algorithm based on the chemotaxis process of Echerichia coil is developed to solve multiobjective optimization problems. The algorithm uses fast nondominated sorting procedure, communication between the colony members and a simple chemotactical strategy to change the bacterial positions in order to explore the search space to find several optimal solutions. The proposed algorithm is validated using 11 benchmark problems and implementing three different performance measures to compare its performance with the NSGA-II genetic algorithm and with the particle swarm-based algorithm NSPSO. (C) 2009 Elsevier Ltd. All rights reserved. National University of Colombia (Universidad Nacional de Colombia) National Council of Technological and Scientific Development (Conselho Nacional de Desenvolvimento Cientifico e Tecnologico-CNPq) |
| Identificador |
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE, v.23, n.3, p.292-301, 2010 0952-1976 http://producao.usp.br/handle/BDPI/17784 10.1016/j.engappai.2009.09.010 |
| Idioma(s) |
eng |
| Publicador |
PERGAMON-ELSEVIER SCIENCE LTD |
| Relação |
Engineering Applications of Artificial Intelligence |
| Direitos |
restrictedAccess Copyright PERGAMON-ELSEVIER SCIENCE LTD |
| Palavras-Chave | #Multiobjective optimization #Bacterial chemotaxis #Bio-inspired techniques #Pareto Optimal Front #Chemotactical strategy optimization #PARTICLE SWARM OPTIMIZATION #DISTRIBUTED OPTIMIZATION #FORAGING OPTIMIZATION #BIOMIMICRY #Automation & Control Systems #Computer Science, Artificial Intelligence #Engineering, Multidisciplinary #Engineering, Electrical & Electronic |
| Tipo |
article original article publishedVersion |
