Allocation planning under service-level contracts |
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| Institution: | 1. Chair of Logistics and Quantitative Methods, Julius-Maximilians-Universität Würzburg, Sanderring 2, Würzburg 97070, Germany;2. MIT-Zaragoza International Logistics Program, Zaragoza Logistics Center, Edificio Náyade 5, C/ Bari 55 (PLAZA), Zaragoza 50197, Spain;1. School of Business, Stevens Institute of Technology, 1 Castle Point Terrace, Hoboken, NJ 07030, USA;2. Lally School of Management, Rensselaer Polytechnic Institute, 110 8th Street, Pittsburgh Building, Troy, NY 12180, USA;3. Division of Economic and Risk Analysis, US Securities and Exchange Commission, 100 F St NE, Washington DC 20549, USA;4. Department of Electrical, Computer & Systems Engineering, Rensselaer Polytechnic Institute, Jonsson Engineering Center 6048, Troy, NY 12180, USA;1. Carey Business School, Johns Hopkins University, 100 International Drive, Baltimore, MD 21202, United States;2. Department of Information Systems and Business Analytics, Florida International University, Miami, FL 33199, United States;1. College of Auditing and Evaluation, Nanjing Audit University, Nanjing, Jiangsu Province, 211815, China;2. Schulich School of Business, York University, Toronto, Ontario M3J 1P3, Canada;3. Foisie Business School, Worcester Polytechnic Institute, Worcester, MA 01609, USA;1. Leiden University Mathematical Institute, Niels Bohrweg 1, 2333 CA, Leiden, NL, UK;2. Department of Management Science, Center for Transportation and Logistics, Lancaster University Management School, Bailrigg, Lancaster LA1 4YX, UK;1. Department of Finance, National Central University, Taiwan;2. Department of Finance, National Taiwan University, Taiwan;3. Department of International Business, National Taiwan University, Taiwan;4. Chinese Academy of Mathematics and Systems Science, China |
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| Abstract: | Motivated by the practical limitations of current demand fulfillment systems, this paper addresses the problem of allocation planning under service-level contracts in a multi-period setting. We provide a formal definition of the allocation planning problem under a type of service-level contract that is particularly relevant to manufacturing industries and formulate a corresponding stochastic dynamic program. Based on a rigorous formal analysis of the dynamic program, we derive the requirements a “good” allocation policy should meet and use them to evaluate the heuristic policies proposed in the literature and to derive new allocation policies that may enhance the performance of allocation planning under service-level contracts. After detailed characterization and discussion of these new policies, we present the results of an extensive numerical study that allow us to quantify and compare allocation policies’ performance and to derive recommendations for decision makers in practice. |
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