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Modeling the Decision and Coordination Mechanism of Power Battery Closed-Loop Supply Chain Using Markov Decision Processes

Author

Listed:
  • Huanyong Zhang

    (School of Business, Jiangnan University, Wuxi 214122, China)

  • Ningshu Li

    (School of Business, Jiangnan University, Wuxi 214122, China)

  • Jinghan Lin

    (School of Business, Jiangnan University, Wuxi 214122, China)

Abstract

With the rapid growth of the new energy vehicle market, efficient management of the closed-loop supply chain of power batteries has become an important issue. Effective closed-loop supply chain management is very critical, which is related to the efficient utilization of resources, environmental responsibility, and the realization of economic benefits. In this paper, the Markov Decision Process (MDP) is used to model the decision-making and coordination mechanism of the closed-loop supply chain of power batteries in order to cope with the challenges in the management process, such as cost, quality, and technological progress. By constructing the MDP model for different supply chain participants, this paper investigates the optimization strategy of the supply chain and applies two solution methods: dynamic programming and reinforcement learning. The case study results show that the model can effectively identify optimized supply chain decisions, improve the overall efficiency of the supply chain, and coordinate the interests among parties. The contribution of this study is to provide a new modeling framework for power battery recycling and to demonstrate the practicality and effectiveness of the method with empirical data. This study demonstrates that the Markov decision-making process can be a powerful tool for closed-loop supply chain management, promotes a deeper understanding of the complex decision-making environment of the supply chain, and provides a new solution path for decision-making and coordination in the supply chain.

Suggested Citation

  • Huanyong Zhang & Ningshu Li & Jinghan Lin, 2024. "Modeling the Decision and Coordination Mechanism of Power Battery Closed-Loop Supply Chain Using Markov Decision Processes," Sustainability, MDPI, vol. 16(11), pages 1-19, May.
  • Handle: RePEc:gam:jsusta:v:16:y:2024:i:11:p:4329-:d:1398678
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    References listed on IDEAS

    as
    1. Maryam Kolyaei & Adel Azar & Ali Rajabzadeh Ghatari, 2023. "An integrated robust optimisation approach to closed-loop supply chain network design under uncertainty: the case of the auto glass industry," International Journal of Process Management and Benchmarking, Inderscience Enterprises Ltd, vol. 14(3), pages 285-310.
    2. Zhangwei Feng & Deyan Yang & Xintian Wang, 2023. "“Internet+ Recycling” Platform Participation Selection Strategy in a Two-Echelon Remanufacturing Closed-Loop Supply Chain," IJERPH, MDPI, vol. 20(5), pages 1-17, February.
    3. Ali Pedram & Shahryar Sorooshian & Freselam Mulubrhan & Afshin Abbaspour, 2023. "Incorporating Vehicle-Routing Problems into a Closed-Loop Supply Chain Network Using a Mixed-Integer Linear-Programming Model," Sustainability, MDPI, vol. 15(4), pages 1-24, February.
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