Adaptive inventory control models for supply chain management |
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Authors: | CO Kim J Jun JK Baek RL Smith YD Kim |
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Affiliation: | 1. School of Computer and Industrial Engineering, Yonsei University, Seoul, 120-749, South Korea 2. Research Institute for Information and Communication Technologies, Korea University, Seoul, 136-701, South Korea 3. Department of Industrial System Management, Seoul College, Seoul, 131-702, South Korea 4. Department of Industrial and Operations Engineering, University of Michigan, Ann Arbor, Michigan, 48109-2117, USA 5. Department of Industrial Engineering, Korea Advanced Institute of Science and Technology, Daejon, 305-701, South Korea
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Abstract: | Uncertainties inherent in customer demands make it difficult for supply chains to achieve just-in-time inventory replenishment, resulting in loosing sales opportunities or keeping excessive chain-wide inventories. In this paper, we propose two adaptive inventory-control models for a supply chain consisting of one supplier and multiple retailers. The one is a centralized model and the other is a decentralized model. The objective of the two models is to satisfy a target service level predefined for each retailer. The inventory-control parameters of the supplier and retailers are safety lead time and safety stocks, respectively. Unlike most extant inventory-control approaches, modelling the uncertainty of customer demand as a statistical distribution is not a prerequisite in the two models. Instead, using a reinforcement learning technique called action-value method, the control parameters are designed to adaptively change as customer-demand patterns changes. A simulation-based experiment was performed to compare the performance of the two inventory-control models. |
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