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dc.contributor.authorSalmeron, Javier
dc.contributor.authorApte, Aruna
dc.dateSeptember - October 2010
dc.date.accessioned2015-04-29T00:28:13Z
dc.date.available2015-04-29T00:28:13Z
dc.date.issued2010
dc.identifier.citationJ. Salmeron and A. Apte, “Stochastic Optimization for Natural Disaster Asset Prepositioning”, Production and Operations Management, 19(5), 2010, pp 561 – 575.en_US
dc.identifier.urihttp://hdl.handle.net/10945/45023
dc.descriptionThe article of record as published may be located at http://dx.doi.org/10.3401/poms.1080.01119en_US
dc.description.abstractA key strategic issue in pre-disaster planning for humanitarian logistics is the pre-establishment of adequate capacity and resources that enable efficient relief operations. This paper develops a two-stage stochastic optimization model to guide the allocation of budget to acquire and position relief assets, decisions that typically need to be made well in advance before a disaster strikes. The optimization focuses on minimizing the expected number of casualties, so our model includes first-stage decisions to represent the expansion of resources such as warehouses, medical facilities with personnel, ramp spaces, and shelters. Second-stage decisions concern the logistics of the problem, where allocated resources and contracted transportation assets are deployed to rescue critical population (in need of emergency evacuation), deliver required commodities to stay-back population, and transport the transfer population displaced by the disaster. Because of the uncertainty of the event’s location and severity, these and other parameters are represented as scenarios. Computational results on notional test cases provide guidance on budget allocation and prove the potential benefit of using stochastic optimization.en_US
dc.rightsThis publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. As such, it is in the public domain, and under the provisions of Title 17, United States Code, Section 105, may not be copyrighted.en_US
dc.titleStochastic Optimization for Natural Disaster Asset Prepositioningen_US
dc.typeArticleen_US
dc.contributor.departmentOperations Researchen_US
dc.contributor.departmentGraduate School of Business & Public Policy (GSBPP)en_US
dc.subject.authorhumanitarian logisticsen_US
dc.subject.authorrelief operationsen_US
dc.subject.authorstochastic optimizationen_US


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