Order Assignment and Resource Reservation: An Optimization Model and Policy Analysis

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dc.contributor.advisorBall, Michael O.en_US
dc.contributor.authorMcNeil, Julie Triciaen_US
dc.contributor.departmentSystems Engineeringen_US
dc.contributor.publisherDigital Repository at the University of Marylanden_US
dc.contributor.publisherUniversity of Maryland (College Park, Md.)en_US
dc.date.accessioned2005-08-03T15:30:15Z
dc.date.available2005-08-03T15:30:15Z
dc.date.issued2005-05-31en_US
dc.description.abstractTo maintain a competitive edge, companies today must be able to efficiently allocate resources to optimally commit and fulfill requested orders. As such, order processing and resource allocation models have become increasingly sophisticated to handle the complexity of these decisions. In our research, we introduce a model that integrates production scheduling, material allocation, delivery scheduling, as well as functions involving commitment of forecast demand for configure-to-order (CTO) and assemble-to-order (ATO) business environments. The model is formulated as a Mixed Integer Program (MIP) and seeks to maximize revenue by trading off commitment of higher profit forecast orders with the production and delivery schedule of lower profit accepted orders. Our model is particularly useful for testing different policies relating to order commitment, delivery mode selection and resource allocation.en_US
dc.format.extent886672 bytes
dc.format.mimetypeapplication/pdf
dc.identifier.urihttp://hdl.handle.net/1903/2668
dc.language.isoen_US
dc.subject.pqcontrolledEngineering, System Scienceen_US
dc.subject.pquncontrolledAvailable-to-Promiseen_US
dc.subject.pquncontrolledOptimization Modelen_US
dc.subject.pquncontrolledOrder Commitmenten_US
dc.titleOrder Assignment and Resource Reservation: An Optimization Model and Policy Analysisen_US
dc.typeThesisen_US

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