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Article: Real-coded chemical reaction optimization

TitleReal-coded chemical reaction optimization
Authors
KeywordsChemical Reaction Optimization
Continuous Optimization
Metaheuristics
Issue Date2012
Citation
IEEE Transactions on Evolutionary Computation, 2012, v. 16 n. 3, p. 339-353 How to Cite?
AbstractOptimization problems can generally be classified as continuous and discrete, based on the nature of the solution space. A recently developed chemical-reaction-inspired metaheuristic, called chemical reaction optimization (CRO), has been shown to perform well in many optimization problems in the discrete domain. This paper is dedicated to proposing a real-coded version of CRO, namely, RCCRO, to solve continuous optimization problems. We compare the performance of RCCRO with a large number of optimization techniques on a large set of standard continuous benchmark functions. We find that RCCRO outperforms all the others on the average. We also propose an adaptive scheme for RCCRO which can improve the performance effectively. This shows that CRO is suitable for solving problems in the continuous domain. © 2012 IEEE.
Persistent Identifierhttp://hdl.handle.net/10722/155765
ISSN
2023 Impact Factor: 11.7
2023 SCImago Journal Rankings: 5.209
ISI Accession Number ID
Funding AgencyGrant Number
Strategic Research Theme of Information Technology of University of Hong Kong
Croucher Foundation
Funding Information:

This work was supported in part by the Strategic Research Theme of Information Technology of the University of Hong Kong. The work of A. Y. S. Lam was also supported in part by the Croucher Foundation Research Fellowship.

References

 

DC FieldValueLanguage
dc.contributor.authorLam, AYSen_US
dc.contributor.authorLi, VOKen_US
dc.contributor.authorYu, JJQen_US
dc.date.accessioned2012-08-08T08:35:14Z-
dc.date.available2012-08-08T08:35:14Z-
dc.date.issued2012en_US
dc.identifier.citationIEEE Transactions on Evolutionary Computation, 2012, v. 16 n. 3, p. 339-353en_US
dc.identifier.issn1089-778Xen_US
dc.identifier.urihttp://hdl.handle.net/10722/155765-
dc.description.abstractOptimization problems can generally be classified as continuous and discrete, based on the nature of the solution space. A recently developed chemical-reaction-inspired metaheuristic, called chemical reaction optimization (CRO), has been shown to perform well in many optimization problems in the discrete domain. This paper is dedicated to proposing a real-coded version of CRO, namely, RCCRO, to solve continuous optimization problems. We compare the performance of RCCRO with a large number of optimization techniques on a large set of standard continuous benchmark functions. We find that RCCRO outperforms all the others on the average. We also propose an adaptive scheme for RCCRO which can improve the performance effectively. This shows that CRO is suitable for solving problems in the continuous domain. © 2012 IEEE.en_US
dc.languageengen_US
dc.relation.ispartofIEEE Transactions on Evolutionary Computationen_US
dc.subjectChemical Reaction Optimizationen_US
dc.subjectContinuous Optimizationen_US
dc.subjectMetaheuristicsen_US
dc.titleReal-coded chemical reaction optimizationen_US
dc.typeArticleen_US
dc.identifier.emailLi, VOK:vli@eee.hku.hken_US
dc.identifier.authorityLi, VOK=rp00150en_US
dc.description.naturelink_to_subscribed_fulltexten_US
dc.identifier.doi10.1109/TEVC.2011.2161091en_US
dc.identifier.scopuseid_2-s2.0-84861817748en_US
dc.identifier.hkuros210451-
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-84861817748&selection=ref&src=s&origin=recordpageen_US
dc.identifier.volume16en_US
dc.identifier.issue3en_US
dc.identifier.spage339en_US
dc.identifier.epage353en_US
dc.identifier.isiWOS:000304823400003-
dc.publisher.placeUnited Statesen_US
dc.identifier.scopusauthoridLam, AYS=35322184700en_US
dc.identifier.scopusauthoridLi, VOK=7202621685en_US
dc.identifier.scopusauthoridYu, JJQ=51865147800en_US
dc.identifier.issnl1089-778X-

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