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http://dx.doi.org/10.12812/ksms.2014.16.4.323

Reinforcement leaning based multi-echelon supply chain distribution planning  

Kwon, Ick-Hyun (Department of Industrial and Management Engineering, Inje University)
Publication Information
Journal of the Korea Safety Management & Science / v.16, no.4, 2014 , pp. 323-330 More about this Journal
Abstract
Various inventory control theories have tried to modelling and analyzing supply chains by using quantitative methods and characterization of optimal control policies. However, despite of various efforts in this research filed, the existing models cannot afford to be applied to the realistic problems. The most unrealistic assumption for these models is customer demand. Most of previous researches assume that the customer demand is stationary with a known distribution, whereas, in reality, the customer demand is not known a priori and changes over time. In this paper, we propose a reinforcement learning based adaptive echelon base-stock inventory control policy for a multi-stage, serial supply chain with non-stationary customer demand under the service level constraint. Using various simulation experiments, we prove that the proposed inventory control policy can meet the target service level quite well under various experimental environments.
Keywords
Multi-echelon; Serial Supply Chain; Base-stock; Non-stationary Demand; Service Level;
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