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dc.contributor.authorChang, Yung-Chiaen_US
dc.contributor.authorChang, Kuei-Huen_US
dc.contributor.authorChang, Teng-Kaien_US
dc.date.accessioned2014-12-08T15:31:13Z-
dc.date.available2014-12-08T15:31:13Z-
dc.date.issued2013-07-01en_US
dc.identifier.issn0020-7543en_US
dc.identifier.urihttp://dx.doi.org/10.1080/00207543.2013.774476en_US
dc.identifier.urihttp://hdl.handle.net/11536/22224-
dc.description.abstractMore and more enterprises have chosen to adopt a made-to-order business model in order to satisfy diverse and rapidly changing customer demand. In such a business model, enterprises are devoted to reducing inventory levels in order to upgrade the competitiveness of the products. However, reductions in inventory levels and short lead times force the operation between production and distribution to cooperate closely, thus increasing the practicability of integrating the production and distribution stages. The complexity of supply chain scheduling problems (integrated production and distribution scheduling) is known to be NP-hard. To address the issues above, an efficient algorithm to solve the supply chain scheduling problem is needed. This paper studies a supply chain scheduling problem in which the production stage is modelled by an identical parallel machine scheduling problem and the distribution stage is modelled by a capacitated vehicle routing problem. Given a set of customer orders (jobs), the problem is to find a supply chain schedule such that the weighted summation of total job weighted completion time and total job delivering cost are minimised. The studied problem was first formulated as an integer programme and then solved by using column generation techniques in conjunction with a branch-and-bound approach to optimality. The results of the computational experiments indicate that the proposed approach can solve the test problems to optimality. Moreover, the average gap between the optimal solutions and the lower bounds is no more than 1.32% for these test problems.en_US
dc.language.isoen_USen_US
dc.subjectdynamic programmingen_US
dc.subjectcolumn generation approachen_US
dc.subjectidentical parallel machineen_US
dc.subjectsupply chain schedulingen_US
dc.titleApplied column generation-based approach to solve supply chain scheduling problemsen_US
dc.typeArticleen_US
dc.identifier.doi10.1080/00207543.2013.774476en_US
dc.identifier.journalINTERNATIONAL JOURNAL OF PRODUCTION RESEARCHen_US
dc.citation.volume51en_US
dc.citation.issue13en_US
dc.citation.spage4070en_US
dc.citation.epage4086en_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:000321900200016-
dc.citation.woscount2-
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