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dc.contributor.authorMansouri, SA-
dc.contributor.authorGallear, D-
dc.contributor.authorAskariazad, MH-
dc.date.accessioned2014-07-15T13:04:17Z-
dc.date.available2014-07-15T13:04:17Z-
dc.date.issued2012-
dc.identifier.citationInternational Journal of Production Economics, 135(1), 24 - 36, 2012en_US
dc.identifier.issn0925-5273-
dc.identifier.urihttp://www.sciencedirect.com/science/article/pii/S0925527310004457en
dc.identifier.urihttp://bura.brunel.ac.uk/handle/2438/8687-
dc.descriptionThis is the post-print version of the final paper published in International Journal of Production Economics. The published article is available from the link below. 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. Copyright @ 2010 Elsevier B.V.en_US
dc.description.abstractThis paper aims to identify the gaps in decision-making support based on multiobjective optimization (MOO) for build-to-order supply chain management (BTO-SCM). To this end, it reviews the literature available on modelling build-to-order supply chains (BTO-SC) with the focus on adopting MOO techniques as a decision support tool. The literature has been classified based on the nature of the decisions in different part of the supply chain, and the key decision areas across a typical BTO-SC are discussed in detail. Available software packages suitable for supporting decision making in BTO supply chains are also identified and their related solutions are outlined. The gap between the modelling and optimization techniques developed in the literature and the decision support needed in practice are highlighted. Future research directions to better exploit the decision support capabilities of MOO are proposed. These include: reformulation of the extant optimization models with a MOO perspective, development of decision supports for interfaces not involving manufacturers, development of scenarios around service-based objectives, development of efficient solution tools, considering the interests of each supply chain party as a separate objective to account for fair treatment of their requirements, and applying the existing methodologies on real-life data sets.en_US
dc.description.sponsorshipBrunel Research Initiative and Enterprise Fund (BRIEF)en_US
dc.language.isoenen_US
dc.publisherElsevieren_US
dc.subjectSupply chain managementen_US
dc.subjectBuild-to-orderen_US
dc.subjectDecision supporten_US
dc.subjectMultiobjective optimizationen_US
dc.subjectPareto-optimal fronten_US
dc.titleDecision support for build-to-order supply chain management through multiobjective optimizationen_US
dc.typeArticleen_US
dc.identifier.doihttp://dx.doi.org/10.1016/j.ijpe.2010.11.016-
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Brunel Business School Research Papers

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