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A competitive-cooperation coevolutionary paradigm for multi-objective optimization

Research output: Chapters, Conference Papers, Creative and Literary WorksRGC 32 - Refereed conference paper (with host publication)peer-review

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.
Original languageEnglish
Title of host publication2007 IEEE 22nd International Symposium on Intelligent Control
PublisherIEEE
Pages255-260
ISBN (Electronic)978-1-4244-0441-4
ISBN (Print)978-1-4244-0440-7
DOIs
Publication statusPublished - Oct 2007
Externally publishedYes
Event2007 IEEE 22nd International Symposium on Intelligent Control (ISIC 2007) - Singapore, Singapore
Duration: 1 Oct 20073 Oct 2007

Conference

Conference2007 IEEE 22nd International Symposium on Intelligent Control (ISIC 2007)
Abbreviated titleISIC 2007
PlaceSingapore
CitySingapore
Period1/10/073/10/07

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