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dc.contributor.author이영해-
dc.date.accessioned2021-01-27T04:49:42Z-
dc.date.available2021-01-27T04:49:42Z-
dc.date.issued2002-07-
dc.identifier.citationCOMPUTERS & INDUSTRIAL ENGINEERING, v. 43, issue. 1-2, page. 169-190en_US
dc.identifier.issn0360-8352-
dc.identifier.urihttps://www.sciencedirect.com/science/article/pii/S0360835202000633-
dc.identifier.urihttps://repository.hanyang.ac.kr/handle/20.500.11754/157613-
dc.description.abstractAnalytic models have been developed to solve the integrated production–distribution problems in supply chain management (SCM). As one of the major constraints in analytic models, operation time has mostly been known or disregarded. However, in the real systems, due to the various kinds of uncertain factors such as unexpected delays, queuing, breakdowns, operation time in the analytic model cannot correctly represent the dynamic behavior of the consumption of real operation time. To solve this problem, in this paper, we propose a hybrid approach combining the analytic and simulation model. Operation time in the analytic model is considered as a dynamic factor and adjusted by the results from independently developed simulation model, which includes general production–distribution characteristics. We obtain the more realistically optimal production–distribution plans for the integrated supply chain system reflecting stochastic natures by performing the iterative hybrid analytic–simulation procedure.en_US
dc.language.isoen_USen_US
dc.publisherPERGAMON-ELSEVIER SCIENCE LTDen_US
dc.subjectSupply chain managementen_US
dc.subjectProduction–distribution planningen_US
dc.subjectHybrid approachen_US
dc.titleProduction-distribution planning in supply chain considering capacity constraintsen_US
dc.typeArticleen_US
dc.identifier.doi10.1016/S0360-8352(02)00063-3-
dc.relation.journalCOMPUTERS & INDUSTRIAL ENGINEERING-
dc.contributor.googleauthorLee, Young Hae-
dc.contributor.googleauthorKim, Sook Han-
dc.relation.code2009202218-
dc.sector.campusE-
dc.sector.daehakCOLLEGE OF ENGINEERING SCIENCES[E]-
dc.sector.departmentDEPARTMENT OF INDUSTRIAL AND MANAGEMENT ENGINEERING-
dc.identifier.pidyhlee-
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COLLEGE OF ENGINEERING SCIENCES[E](공학대학) > INDUSTRIAL AND MANAGEMENT ENGINEERING(산업경영공학과) > Articles
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