A profit maximization model in a two-echelon supply chain management : distribution and pricing strategies
Author(s)
Mao, Ye, 1978-
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Other Contributors
Massachusetts Institute of Technology. Operations Research Center.
Advisor
Donald B. Rosenfield Joseph R. Sussman.
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Distribution and pricing strategies play a central role in the field of supply chain management. Heuristic approaches to the vehicle routing problem (VRP) are usually used to design optimal delivery routes to serve geographically dispersed customers, who are price elastic. There is a rich literature discussing either the manufacturer's distribution strategy or its pricing initiatives. The purpose of this thesis is to develop a profit maximization model that presents an integrated distribution and pricing strategy for any company facing such issues. We first examine a simplified scenario when all customers are located in the same delivery region and their demand is deterministic. Both truckload (TL) and less-than-truckload (LTL) shipment strategies are analyzed and compared. We later extend our findings to multiple delivery regions and discuss the impact of the manufacturer's pricing flexibility on its profit. Then we relax the assumption of deterministic customer demand and introduce the safety stock cost. Finally the application on across delivery region situations is shown. Although some of our assumptions simplify our model, we believe that it provides insight into more complex supply chain management problems.
Description
Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Civil and Environmental Engineering; and, (S.M.)--Massachusetts Institute of Technology, Sloan School of Management, Operations Research Center, 2003. Includes bibliographical references (p. 109-111).
Date issued
2003Department
Massachusetts Institute of Technology. Department of Civil and Environmental Engineering; Massachusetts Institute of Technology. Operations Research Center; Sloan School of ManagementPublisher
Massachusetts Institute of Technology
Keywords
Civil and Environmental Engineering., Operations Research Center.