Optimization Models for Integrated Production, Capacity and Revenue Management

Download or read book Optimization Models for Integrated Production, Capacity and Revenue Management written by Yasemin Merzifonluoglu and published by . This book was released on 2006 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: ABSTRACT: This thesis provides new planning models for making synchronized decisions on capacity, demand management and production/inventory planning in supply chains. These models focus on the tradeoffs between capacity costs, production costs, costs for assigning customer demands to different supply resources and revenues associated with satisfying customer demands. Within this class of models, we study various degrees of flexibility on the part of a supplier of goods, including flexibility in demand and capacity management. We consider integrated production, capacity, and pricing planning problems, where a good's price may change throughout a planning horizon, as well as contexts in which a constant price is required for the entire horizon. We also consider production planning models in which a supplier may not have a great deal of price setting flexibility, but may wish to be selective in its choice of markets (or customers) and the timing of demand fulfillment, as a result of the unique fulfillment costs associated with different markets (or customers). We also investigate the role of capacity planning in these contexts, including capacity acquisition problems that require setting the supplier's best capacity level for an entire planning horizon. We examine subcontracting and overtime as mechanisms for short-term capacity flexibility. We also consider logistics supply network design problems that determine the best allocation of downstream demands to upstream facilities in uncertain demand environments. We used polyhedral properties and dynamic programming techniques to provide polynomial-time solution approaches for obtaining optimal solutions for some of the problems that are not NP-Hard. When the problem is NP-Hard, we proposed very efficient heuristic solution approaches which are developed considering particular features of the problems. We also employed a Branch and Price method for the large scale nonlinear assignment problems.