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Article: A hybrid generic algorithm for production and distribution

TitleA hybrid generic algorithm for production and distribution
Authors
Issue Date2005
PublisherPergamon. The Journal's web site is located at http://www.elsevier.com/locate/omega
Citation
Omega, 2005, v. 33 n. 4, p. 345-355 How to Cite?
AbstractThis paper develops a hybrid genetic algorithm for production and distribution problems in multi-factory supply chain models. Supply chain problems usually may involve multi-criterion decision-making, for example operating cost, service level, resources utilization, etc. These criteria are numerous and interrelated. To organize them, analytic hierarchy process (AHP) will be utilized. It provides a systematic approach for decision makers to assign weightings and relate them. Meanwhile, genetic algorithms (GAs) will be utilized to determine jobs allocation into suitable production plants. Genetic operators adopted to improve the genetic search algorithm will be introduced and discussed. Finally, a hypothetical production–distribution problem will be solved by the proposed algorithm. The optimization results show that it is reliable and robust.
Persistent Identifierhttp://hdl.handle.net/10722/74608
ISSN
2015 Impact Factor: 3.962
2015 SCImago Journal Rankings: 3.771

 

DC FieldValueLanguage
dc.contributor.authorChan, FTS-
dc.contributor.authorChung, SH-
dc.contributor.authorWadhwa, S-
dc.date.accessioned2010-09-06T07:03:01Z-
dc.date.available2010-09-06T07:03:01Z-
dc.date.issued2005-
dc.identifier.citationOmega, 2005, v. 33 n. 4, p. 345-355-
dc.identifier.issn0305-0483-
dc.identifier.urihttp://hdl.handle.net/10722/74608-
dc.description.abstractThis paper develops a hybrid genetic algorithm for production and distribution problems in multi-factory supply chain models. Supply chain problems usually may involve multi-criterion decision-making, for example operating cost, service level, resources utilization, etc. These criteria are numerous and interrelated. To organize them, analytic hierarchy process (AHP) will be utilized. It provides a systematic approach for decision makers to assign weightings and relate them. Meanwhile, genetic algorithms (GAs) will be utilized to determine jobs allocation into suitable production plants. Genetic operators adopted to improve the genetic search algorithm will be introduced and discussed. Finally, a hypothetical production–distribution problem will be solved by the proposed algorithm. The optimization results show that it is reliable and robust.-
dc.languageeng-
dc.publisherPergamon. The Journal's web site is located at http://www.elsevier.com/locate/omega-
dc.relation.ispartofOmega-
dc.rightsNOTICE: this is the author’s version of a work that was accepted for publication in [Journal title]. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in PUBLICATION, [VOL#, ISSUE#, (DATE)] DOI# -
dc.subject.meshAcetylgalactosamine - immunology-
dc.subject.meshAntibodies, Monoclonal - immunology-
dc.subject.meshAntibodies, Neoplasm - immunology-
dc.subject.meshFibrosarcoma - chemically induced - immunology-
dc.subject.meshEpitopes - immunology-
dc.titleA hybrid generic algorithm for production and distribution-
dc.typeArticle-
dc.identifier.emailChan, FTS: ftschan@hkucc.hku.hk-
dc.identifier.authorityChan, FTS=rp00090-
dc.identifier.doi10.1016/j.omega.2004.05.004-
dc.identifier.pmid1708163-
dc.identifier.hkuros100468-
dc.identifier.volume33-
dc.identifier.issue4-
dc.identifier.spage345-
dc.identifier.epage355-
dc.publisher.placeUnited Kingdom-

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