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dc.contributor.authorChang, Yung-Chiaen_US
dc.contributor.authorLi, Vincent C.en_US
dc.contributor.authorChiang, Chia-Juen_US
dc.date.accessioned2014-12-08T15:35:19Z-
dc.date.available2014-12-08T15:35:19Z-
dc.date.issued2014-04-03en_US
dc.identifier.issn0305-215Xen_US
dc.identifier.urihttp://dx.doi.org/10.1080/0305215X.2013.786062en_US
dc.identifier.urihttp://hdl.handle.net/11536/23944-
dc.description.abstractMake-to-order or direct-order business models that require close interaction between production and distribution activities have been adopted by many enterprises in order to be competitive in demanding markets. This article considers an integrated production and distribution scheduling problem in which jobs are first processed by one of the unrelated parallel machines and then distributed to corresponding customers by capacitated vehicles without intermediate inventory. The objective is to find a joint production and distribution schedule so that the weighted sum of total weighted job delivery time and the total distribution cost is minimized. This article presents a mathematical model for describing the problem and designs an algorithm using ant colony optimization. Computational experiments illustrate that the algorithm developed is capable of generating near-optimal solutions. The computational results also demonstrate the value of integrating production and distribution in the model for the studied problem.en_US
dc.language.isoen_USen_US
dc.subjectintegrated schedulingen_US
dc.subjectproduction and distribution operationsen_US
dc.subjectunrelated parallel machinesen_US
dc.subjectant colony optimizationen_US
dc.titleAn ant colony optimization heuristic for an integrated production and distribution scheduling problemen_US
dc.typeArticleen_US
dc.identifier.doi10.1080/0305215X.2013.786062en_US
dc.identifier.journalENGINEERING OPTIMIZATIONen_US
dc.citation.volume46en_US
dc.citation.issue4en_US
dc.citation.spage503en_US
dc.citation.epage520en_US
dc.contributor.department工業工程與管理學系zh_TW
dc.contributor.departmentDepartment of Industrial Engineering and Managementen_US
dc.identifier.wosnumberWOS:000331336800004-
dc.citation.woscount1-
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