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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Kim, C., Jun, J., Baek, J. et al. Adaptive inventory control models for supply chain management. Int J Adv Manuf Technol 26, 1184–1192 (2005). https://doi.org/10.1007/s00170-004-2069-8
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DOI: https://doi.org/10.1007/s00170-004-2069-8