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Supply chain network optimization for emergency materials considering demand satisfaction

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  • Jindi Huang
  • Wuyong Qian
  • Minghao Ran

Abstract

In order to effectively guarantee the smooth supply of emergency materials under public health emergencies, first, we predict the number of daily infected people based on the modified SEIRD infectious disease dynamics model and accordingly construct the dynamic demand prediction model of emergency materials so as to catch the change rule of the demand for emergency materials with greater precision. Subsequently, under the premise of demand satisfaction, we optimize the supply chain network of emergency materials and embed two insurance strategies in the supply system in advance: multi‐source purchase and buffer production capacity, to enhance the stability of supply chain by sacrificing part of the cost. Next, a bi‐objective linear programming model based on minimizing system cost and maximizing demand satisfaction is proposed with the intention of realizing the design of emergency materials supply chain network, which balances the risk and cost. Finally, through the analysis of the example, we find that compared with the traditional supply chain network of emergency materials, the total satisfaction rate of the supply chain network optimized by balancing cost and risk is increased by 11.70%, while the cost is increased by only 2.04%, which fully verifies the validity of the optimized design of supply chain network of emergency materials.

Suggested Citation

  • Jindi Huang & Wuyong Qian & Minghao Ran, 2024. "Supply chain network optimization for emergency materials considering demand satisfaction," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 45(6), pages 3805-3817, September.
    • Handle: RePEc:wly:mgtdec:v:45:y:2024:i:6:p:3805-3817
    DOI: 10.1002/mde.4220
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    References listed on IDEAS

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    1. Barbosa-Póvoa, Ana Paula & da Silva, Cátia & Carvalho, Ana, 2018. "Opportunities and challenges in sustainable supply chain: An operations research perspective," European Journal of Operational Research, Elsevier, vol. 268(2), pages 399-431.
    2. Shaoqing Geng & Hanping Hou, 2021. "Demand Stratification and Prediction of Evacuees after Earthquakes," Sustainability, MDPI, vol. 13(16), pages 1-22, August.
    3. Alem, Douglas & Clark, Alistair & Moreno, Alfredo, 2016. "Stochastic network models for logistics planning in disaster relief," European Journal of Operational Research, Elsevier, vol. 255(1), pages 187-206.
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    1. Haonan Xu & Jiaguo Liu, 2025. "Pricing and Procurement Strategies for Substitute Products in Extreme Weather," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 46(3), pages 1871-1887, April.

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