期刊
EXPERT SYSTEMS WITH APPLICATIONS
卷 202, 期 -, 页码 -出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.eswa.2022.117156
关键词
Scenario-based approach; Economic model predictive control; Inventory; Transportation; Stochastic demands; Supply chain management
类别
资金
- National Key Research and Development Program of China [2020YFB1006104]
- National Natural Science Foundation of China [71773025]
This study proposes a scenario-based economic model predictive control framework for integrated inventory and transportation management in multi-echelon supply chains. The framework provides real-time optimal operations, minimizes operating costs, and guarantees risk probabilities.
The integration of inventory and transportation operations is a challenging task in multi-echelon supply chain management. Uncertainties in customer demands can have serious consequences, such as inventory fluctuations and transportation changes. Policies of integrated inventory and transportation management aim to find a balance between supply and demand and can minimize the total operating cost for the entire supply chain. In this study, we propose a scenario-based economic model predictive control (EMPC) framework for integrated inventory and transportation management of multi-echelon supply chains with stochastic demands. The proposed scenario-based EMPC framework can provide real-time optimal operations for automated inventory and transportation management with a minimum operating cost and a guaranteed risk probability. As the number of scenarios is linked with the risk probability, we develop a design condition to choose the number of scenarios and ensure that optimal operations from the proposed framework can guarantee the desired risk probability. Finally, we present a case study of a three-echelon supply chain benchmark to demonstrate the effectiveness of the proposed EMPC framework and provide several comparison results to show its performance.
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