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Decision Support for Optimal Adaptation of Product and Supply Chain Systems based on Real Options Theory

dc.contributor.authorPark, Chong Hyunen_US
dc.contributor.authorPatil, Laliten_US
dc.contributor.authorSaitou, Kazuhiroen_US
dc.contributor.authorRomeijn, H. Edwinen_US
dc.date.accessioned2011-11-14T16:31:01Z
dc.date.available2011-11-14T16:31:01Z
dc.date.issued2009-08-22en_US
dc.identifier.citationPark, C.-H.; Patil, L.; Saitou, K.; Romeijn, H. E. (2009). Decision Support for Optimal Adaptation of Product and Supply Chain Systems based on Real Options Theory." Proceedings of IEEE Conference on Automation Science and Engineering: <http://hdl.handle.net/2027.42/87256>en_US
dc.identifier.isbn978-1-4244-4578-3en_US
dc.identifier.urihttps://hdl.handle.net/2027.42/87256
dc.description.abstractIn order to remain profitable in the highly competitive global market, a manufacturing enterprise is expected to proactively adapt itself in anticipation of unplanned, but foreseeable high impact events. This paper presents a decision model for optimal adaptation of product and supply chain systems subject to sudden, severe changes in the operating environment. Extending our previous work, decision-tree based framework is developed for optimally choosing design-supplier alternatives in multi-product, multi-echelon product and supply chain systems based on the real options theory. A case study on a two-component, two-echelon supply chain is presented which highlights unique characteristics of product quality as compared to cost and time.en_US
dc.publisherIEEEen_US
dc.titleDecision Support for Optimal Adaptation of Product and Supply Chain Systems based on Real Options Theoryen_US
dc.typeArticleen_US
dc.subject.hlbsecondlevelMechanical Engineeringen_US
dc.subject.hlbtoplevelEngineeringen_US
dc.description.peerreviewedPeer Revieweden_US
dc.contributor.affiliationumThe Industrial and Operations Engineering Departmenten_US
dc.contributor.affiliationumDepartment of Mechanical Engineeringen_US
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/87256/4/Saitou57.pdf
dc.identifier.doi10.1109/COASE.2009.5234119en_US
dc.identifier.sourceProceedings of IEEE Conference on Automation Science and Engineeringen_US
dc.owningcollnameMechanical Engineering, Department of


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