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Article: Chemical Reaction Optimization: A tutorial

TitleChemical Reaction Optimization: A tutorial
Authors
KeywordsApproximate algorithm
Chemical Reaction Optimization
Metaheuristic
Nature-inspired algorithm
Optimization
Issue Date2012
PublisherSpringer. The Journal's web site is located at http://www.springer.com/engineering/journal/12293
Citation
Memetic Computing, 2012, v. 4 n. 1, p. 3-17 How to Cite?
AbstractChemical Reaction Optimization (CRO) is a recently established metaheuristics for optimization, inspired by the nature of chemical reactions. A chemical reaction is a natural process of transforming the unstable substances to the stable ones. In microscopic view, a chemical reaction starts with some unstable molecules with excessive energy. The molecules interact with each other through a sequence of elementary reactions. At the end, they are converted to those with minimum energy to support their existence. This property is embedded in CRO to solve optimization problems. CRO can be applied to tackle problems in both the discrete and continuous domains. We have successfully exploited CRO to solve a broad range of engineering problems, including the quadratic assignment problem, neural network training, multimodal continuous problems, etc. The simulation results demonstrate that CRO has superior performance when compared with other existing optimization algorithms. This tutorial aims to assist the readers in implementing CRO to solve their problems. It also serves as a technical overview of the current development of CRO and provides potential future research directions. © 2012 The Author(s).
Persistent Identifierhttp://hdl.handle.net/10722/147100
ISSN
2023 Impact Factor: 3.3
2023 SCImago Journal Rankings: 0.945
ISI Accession Number ID
References

 

DC FieldValueLanguage
dc.contributor.authorLam, AYSen_HK
dc.contributor.authorLi, VOKen_HK
dc.date.accessioned2012-05-25T07:50:44Z-
dc.date.available2012-05-25T07:50:44Z-
dc.date.issued2012en_HK
dc.identifier.citationMemetic Computing, 2012, v. 4 n. 1, p. 3-17en_HK
dc.identifier.issn1865-9284en_HK
dc.identifier.urihttp://hdl.handle.net/10722/147100-
dc.description.abstractChemical Reaction Optimization (CRO) is a recently established metaheuristics for optimization, inspired by the nature of chemical reactions. A chemical reaction is a natural process of transforming the unstable substances to the stable ones. In microscopic view, a chemical reaction starts with some unstable molecules with excessive energy. The molecules interact with each other through a sequence of elementary reactions. At the end, they are converted to those with minimum energy to support their existence. This property is embedded in CRO to solve optimization problems. CRO can be applied to tackle problems in both the discrete and continuous domains. We have successfully exploited CRO to solve a broad range of engineering problems, including the quadratic assignment problem, neural network training, multimodal continuous problems, etc. The simulation results demonstrate that CRO has superior performance when compared with other existing optimization algorithms. This tutorial aims to assist the readers in implementing CRO to solve their problems. It also serves as a technical overview of the current development of CRO and provides potential future research directions. © 2012 The Author(s).en_HK
dc.languageengen_US
dc.publisherSpringer. The Journal's web site is located at http://www.springer.com/engineering/journal/12293en_US
dc.relation.ispartofMemetic Computingen_HK
dc.rightsThe Author(s)en_US
dc.rightsThis work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.en_US
dc.subjectApproximate algorithmen_HK
dc.subjectChemical Reaction Optimizationen_HK
dc.subjectMetaheuristicen_HK
dc.subjectNature-inspired algorithmen_HK
dc.subjectOptimizationen_HK
dc.titleChemical Reaction Optimization: A tutorialen_HK
dc.typeArticleen_HK
dc.identifier.openurlhttp://www.springerlink.com/link-out/?id=2104&code=Y3774V13P68G6047&MUD=MPen_US
dc.identifier.emailLi, VOK:vli@eee.hku.hken_HK
dc.identifier.authorityLi, VOK=rp00150en_HK
dc.description.naturepublished_or_final_versionen_US
dc.identifier.doi10.1007/s12293-012-0075-1en_HK
dc.identifier.scopuseid_2-s2.0-84857648810en_HK
dc.identifier.hkuros210453-
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-84857648810&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume4en_HK
dc.identifier.issue1en_HK
dc.identifier.spage3en_HK
dc.identifier.epage17en_HK
dc.identifier.eissn1865-9292en_US
dc.identifier.isiWOS:000209099000002-
dc.publisher.placeGermany-
dc.description.otherSpringer Open Choice, 25 May 2012en_US
dc.identifier.scopusauthoridLam, AYS=35322184700en_HK
dc.identifier.scopusauthoridLi, VOK=7202621685en_HK
dc.identifier.issnl1865-9284-

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