Optimal inventory control in a multi-period newsvendor problem with non-stationary demand |
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| Affiliation: | 1. School of MAE, Nanyang Technological University, Singapore;2. Systems Engineering and Operations Research Department, George Mason University, Fairfax, VA 22030, USA;1. Business School, University of Edinburgh, United Kingdom;2. Insight Centre for Data Analytics, University College Cork, Ireland;3. Institute of Population Studies, Hacettepe University, Turkey;4. Department of Computer Engineering, Izmir University of Economics, Turkey;1. College of Business and Administration, Zhejiang University of Technology, Hangzhou, Zhejiang 310023, China;2. Department of Mathematics and Information Science, Binzhou University, Binzhou 256603, China;3. Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hung Hom, Hong Kong;1. School of MAE, Nanyang Technological University, Singapore;2. Google Inc., Mountain View, CA, USA;1. Departamento de Estadística e Investigación Operativa, Facultad de Matemáticas, Instituto de Matemáticas de la Universidad de Sevilla, Av. Reina Mercedes, s/n, 41012 Sevilla, Spain;2. Department of Statistics and Operational Research, Universidad de Cádiz, Spain |
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| Abstract: | The optimal control of inventory in supply chains plays a key role in the competiveness of a corporation. The inventory cost can account for half of company’s logistics cost. The classical inventory models, e.g., newsvendor and EOQ models, assume either a single or infinite planning periods. However, these models may not be applied to perishable products which usually have a certain shelf life. To optimize the total logistic cost for perishable products, this paper presents a multi-period newsvendor model, and the problem is formulated as a multi-stage stochastic programming model with integer recourse decisions. We extend the progressive hedging method to solve the model efficiently. A numerical example and its sensitivity analysis are demonstrated. |
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| Keywords: | Inventory models Newsvendor models Multi-stage stochastic programming Progressive hedging methods |
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