Adaptive inventory control models for supply chain management

C. O. Kim, J. Jun, J. K. Baek, R. L. Smith, Y. D. Kim

Research output: Contribution to journalArticlepeer-review

67 Citations (Scopus)


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.

Original languageEnglish
Pages (from-to)1184-1192
Number of pages9
JournalInternational Journal of Advanced Manufacturing Technology
Issue number9-10
Publication statusPublished - 2005 Oct

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Software
  • Mechanical Engineering
  • Computer Science Applications
  • Industrial and Manufacturing Engineering


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