Please use this identifier to cite or link to this item: https://doi.org/10.1109/ISIC.2007.4450894
Title: A competitive-cooperation coevolutionary paradigm for multi-objective optimization
Authors: Goh, C.K.
Tan, K.C. 
Tay, E.B. 
Issue Date: 2008
Source: Goh, C.K.,Tan, K.C.,Tay, E.B. (2008). A competitive-cooperation coevolutionary paradigm for multi-objective optimization. 22nd IEEE International Symposium on Intelligent Control, ISIC 2007. Part of IEEE Multi-conference on Systems and Control : 255-260. ScholarBank@NUS Repository. https://doi.org/10.1109/ISIC.2007.4450894
Abstract: This paper proposes a new coevolutionary paradigm that hybridizes competitive and cooperative mechanisms observed in nature to solve multi-objective optimization problems. The main idea of cooperationist- competitive revolution is to allow the decomposition process of the optimization problem to adapt and emerge rather than being hand designed and fixed at the start of the evolutionary optimization process. In particular, each species subpopulation will compete to represent a particular subcomponent of the multi-objective problem while the eventual winners will cooperate to evolve the better solutions. The effectiveness of the competitive-cooperation coevolutionary algorithm (COEA) is validated against various multi-objective evolutionary algorithms upon three benchmark problems characterized by different difficulties in local optimality, non-convexity and high-dimensionality. © 2007 IEEE.
Source Title: 22nd IEEE International Symposium on Intelligent Control, ISIC 2007. Part of IEEE Multi-conference on Systems and Control
URI: http://scholarbank.nus.edu.sg/handle/10635/68748
ISBN: 142440441X
DOI: 10.1109/ISIC.2007.4450894
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