Please use this identifier to cite or link to this item: http://cmuir.cmu.ac.th/jspui/handle/6653943832/56863
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dc.contributor.authorWapee Manopiniwesen_US
dc.contributor.authorTakashi Iroharaen_US
dc.date.accessioned2018-09-05T03:31:16Z-
dc.date.available2018-09-05T03:31:16Z-
dc.date.issued2017-02-16en_US
dc.identifier.issn1366588Xen_US
dc.identifier.issn00207543en_US
dc.identifier.other2-s2.0-84982824299en_US
dc.identifier.other10.1080/00207543.2016.1211340en_US
dc.identifier.urihttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84982824299&origin=inwarden_US
dc.identifier.urihttp://cmuir.cmu.ac.th/jspui/handle/6653943832/56863-
dc.description.abstract© 2016 Informa UK Limited, trading as Taylor & Francis Group. This paper proposes a stochastic linear mixed-integer programming model for integrated decisions in the preparedness and response stages in pre- and post-disaster operations, respectively. We develop a model for integrated decisions that considers three key areas of emergency logistics: facility and stock prepositioning, evacuation planning and relief vehicle planning. To develop a framework for effective relief operations, we consider not only a cost-based but also an equity-based solution approach in our multiple objectives model. Then a normalised weighted sum method is used to parameterise our multiple objective programming model. This paper suggests a compromise between the cost, and the equity of relief victims. The experiments also demonstrate how time restrictions and the availability of relief vehicles impact the two objective functions.en_US
dc.subjectBusiness, Management and Accountingen_US
dc.subjectDecision Sciencesen_US
dc.subjectEngineeringen_US
dc.titleStochastic optimisation model for integrated decisions on relief supply chains: preparedness for disaster responseen_US
dc.typeJournalen_US
article.title.sourcetitleInternational Journal of Production Researchen_US
article.volume55en_US
article.stream.affiliationsSophia Universityen_US
article.stream.affiliationsChiang Mai Universityen_US
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