China Safety Science Journal ›› 2024, Vol. 34 ›› Issue (3): 222-229.doi: 10.16265/j.cnki.issn1003-3033.2024.03.0625

• Emergency technology and management • Previous Articles     Next Articles

Emergency rescue allocation decision-making based on three-sided matching theory

GUO Qian1(), ZHOU Yike2, WU Gang1,2,**()   

  1. 1 School of Transportation and Logistics, Southwest Jiaotong University, Chengdu Sichuan 611756, China
    2 Tangshan Institute, Southwest Jiaotong University, Tangshan Hebei 063000, China
  • Received:2023-09-20 Revised:2023-12-21 Online:2024-03-28 Published:2024-09-28
  • Contact: WU Gang


To address the issues of allocation of emergency rescuers, emergency rescue equipment, and disaster locations in the early stage of emergency rescue under the background of large-scale geological disasters, as well as improve the efficiency and quality of emergency rescue, an emergency rescue allocation decision-making method was proposed based on the three-sided matching theory. Firstly, the selection process among the three parties of emergency rescue was presented as a three-sided matching issue. Then, the multi-attribute preference evaluation information of the matching three parties was standardized, and a multi-attribute comprehensive preference score matrix was proposed. Furthermore, a three-sided matching stable and satisfactory model in the early stage of emergency rescue was developed to maximize system stability and total preference utility. Finally, the performance and accuracy of the proposed model were validated against cases. The results indicated that the proposed model reached reasonable matching between rescuers, emergency rescue equipment, and disaster locations in emergency rescue scenarios due to considering the effects of various parties' preferences on resource allocation. Furthermore, it can contribute to reducing the deployment time of emergency rescue operations and improve emergency efficiency and quality.

Key words: emergency rescue, three-sided matching, allocation decision, preference value, stable and satisfactory matching model

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