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McDonald’s China Adopts Operations Research for Network Design

Author

Listed:
  • Shouwei Tang

    (Optimization Analytics Technology Pte. Ltd., Singapore 199591)

  • Lei Wang

    (Optimization Analytics Technology Pte. Ltd., Singapore 199591)

  • Yun Shi

    (McDonald’s China, Shanghai 201103, China)

  • Andy Li

    (McDonald’s China, Shanghai 201103, China)

  • Kevin Lin

    (Xianhui Logistics, Shanghai 201801, China)

  • Chen Xiang

    (Optimization Analytics Technology Pte. Ltd., Singapore 199591)

  • Sophia Niu

    (Optimization Analytics Technology Pte. Ltd., Singapore 199591)

  • Shaofeng Zhou

    (Optimization Analytics Technology Pte. Ltd., Singapore 199591)

  • Ming Liu

    (Xianhui Logistics, Shanghai 201801, China)

  • Hank Tang

    (Xianhui Logistics, Shanghai 201801, China)

Abstract

The supply chain network design (SCND) problem is a typical optimization problem that determines the structure of a supply chain and affects its costs and operational performance. SCND deals with various decisions, such as determining the number, size, and location of facilities and the optimal material and product flows of the entire supply chain network. Therefore, SCND is one of the most crucial planning problems in supply chain management. In this paper, we present a practical approach in which we adopt a mixed-integer programming (MIP) mathematical model to solve a real industry SCND problem for McDonald’s China. As a result of this project, McDonald’s China has saved millions of dollars in logistics costs and reduced CO 2 emissions by more than 10%. In our approach, size-reduction techniques were successfully applied to deal with a large-scale model, making it possible to analyze hundreds of scenarios before coming to a consensus.

Suggested Citation

  • Shouwei Tang & Lei Wang & Yun Shi & Andy Li & Kevin Lin & Chen Xiang & Sophia Niu & Shaofeng Zhou & Ming Liu & Hank Tang, 2025. "McDonald’s China Adopts Operations Research for Network Design," Interfaces, INFORMS, vol. 55(1), pages 36-47, January.
    • Handle: RePEc:inm:orinte:v:55:y:2025:i:1:p:36-47
    DOI: 10.1287/inte.2024.0179
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