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Supply–Demand Matching of Engineering Construction Materials in Complex Mountainous Areas Based on Complex Environment Two-Stage Stochastic Programing

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Listed:
  • Liu Bao

    (Faculty of Geosciences and Engineering, Southwest Jiaotong University, Chengdu 611756, China)

  • Peigen Zhang

    (School of Transportation and Logistics, Southwest Jiaotong University, Chengdu 611756, China)

  • Ze Guo

    (Institute of Computing Technologies, China Academy of Railway Science Corporation Limited, Beijing 100081, China)

  • Wanqi Wang

    (Institute of Computing Technologies, China Academy of Railway Science Corporation Limited, Beijing 100081, China)

  • Qing Zhu

    (Faculty of Geosciences and Engineering, Southwest Jiaotong University, Chengdu 611756, China)

  • Yulin Ding

    (Faculty of Geosciences and Engineering, Southwest Jiaotong University, Chengdu 611756, China)

Abstract

Effective supply and demand matching for construction materials is a crucial challenge in large-scale railway projects, particularly in complex and hazardous environments. We propose a two-stage stochastic programing model that incorporates environmental uncertainties, such as natural disasters, into the supply chain optimization process. The first stage determines optimal locations and capacities for material supply points, while the second stage addresses material distribution under uncertain demand. We further enhance the model’s efficiency with Benders decomposition algorithm. The performance of our model is rigorously compared with existing optimization approaches, demonstrating its superior capability in handling environmental uncertainties and complex logistical scenarios. This study provides a novel framework for optimizing supply chains in challenging environments, offering significant improvements over traditional models in both adaptability and robustness.

Suggested Citation

  • Liu Bao & Peigen Zhang & Ze Guo & Wanqi Wang & Qing Zhu & Yulin Ding, 2024. "Supply–Demand Matching of Engineering Construction Materials in Complex Mountainous Areas Based on Complex Environment Two-Stage Stochastic Programing," Mathematics, MDPI, vol. 12(17), pages 1-14, August.
  • Handle: RePEc:gam:jmathe:v:12:y:2024:i:17:p:2683-:d:1466494
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    References listed on IDEAS

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