Adaptive inventory control models for supply chain management

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 customerdemand patterns changes. A simulation-based experiment was C.O. Kim ( ) School of Computer and Industrial Engineering, Yonsei University, Seoul, 120-749, Republic of Korea E-mail: [email protected] Tel: (+822) 2123-2711 Fax: (+822) 364-7807 J. Jun Research Institute for Information and Communication Technologies, Korea University, Seoul, 136-701, Republic of Korea J.K. Baek Department of Industrial System Management, Seoul College, Seoul, 131-702, Republic of Korea R.L. Smith Department of Industrial and Operations Engineering, University of Michigan, Ann Arbor, Michigan 48109-2117, USA Y.D. Kim Department of Industrial Engineering, Korea Advanced Institute of Science and Technology, Daejon, 305-701, Republic of Korea performed to compare the performance of the two inventorycontrol models.