Please use this identifier to cite or link to this item: http://hdl.handle.net/2440/75170
Citations
Scopus Web of Science® Altmetric
?
?
Full metadata record
DC FieldValueLanguage
dc.contributor.authorIbrahimov, M.en
dc.contributor.authorMohais, A.en
dc.contributor.authorSchellenberg, S.en
dc.contributor.authorMichalewicz, Z.en
dc.date.issued2012en
dc.identifier.citationInternational Journal of Intelligent Computing and Cybernetics, 2012; 5(4):473-499en
dc.identifier.issn1756-378Xen
dc.identifier.issn1756-3798en
dc.identifier.urihttp://hdl.handle.net/2440/75170-
dc.description.abstractPURPOSE – The purpose of this paper and its companion (Part I: single and two-component supply chains) is to investigate methods to tackle complexities, constraints (including time-varying constraints) and other challenges. In this part, attention is devoted to multi-silo supply chain and the relationships between the components. The first part of the paper aims to consider two types of experimental supply chains: with one-to-many and many-to-one relationships. The second half of the paper aims to present two approaches on optimising the material flow in the real-world supply chain network. DESIGN/METHODOLOGY/APPROACH – Cooperative coevolutionary and classical sequential approaches are taken to address the experimental multi-silo supply chains. Due to the nature and the complexity of the supply chain presented in the second half of the paper, evolutionary algorithm was not sufficient to tackle the problem. A fuzzy-evolutionary algorithm is proposed to address the problem. FINDINGS – The proposed systems produce solutions better than solutions proposed by human experts and in much shorter time. ORIGINALITY/VALUE – The paper discusses various algorithms to provide the decision support for the real-world problems. The system proposed for the real-world supply chain is in the process of integration to the production environment.en
dc.description.statementofresponsibilityMaksud Ibrahimov, Arvind Mohais and Sven Schellenberg, Zbigniew Michalewiczen
dc.language.isoenen
dc.publisherEmerald Group Publishing Ltden
dc.rights© Emerald Group Publishing Limiteden
dc.subjectCooperative coevolution; Coordinated supply chain; Genetic algorithms; supply chain management; Time-varying constraints; Time-varying control systemsen
dc.titleEvolutionary approaches for supply chain optimisation. Part II: Multi-silo supply chainsen
dc.typeJournal articleen
dc.identifier.rmid0020123348en
dc.identifier.doi10.1108/17563781211282240en
dc.identifier.pubid22373-
pubs.library.collectionComputer Science publicationsen
pubs.verification-statusVerifieden
pubs.publication-statusPublisheden
Appears in Collections:Computer Science publications

Files in This Item:
There are no files associated with this item.


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.