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A two-stage method for member selection of emergency medical service

Author

Listed:
  • Xi Chen

    (Xidian University)

  • Zhiping Fan

    (Northeastern University)

  • Zhiwu Li

    (Macau University of Science and Technology
    King Abdulaziz University
    Xidian University)

  • Xueliang Han

    (Xidian University)

  • Xiao Zhang

    (Xidian University)

  • Haochen Jia

    (Stony Brook University)

Abstract

Member selection is an important decision making problem in the formation of emergency medical teams. It involves selecting an optimal combination from a reasonable number of doctors, nurses and emergency medical technicians. Selecting suitable members for a medical emergency team (MET) will facilitate the effectiveness of emergency medical service (EMS). Essentially, investigations on EMS could offer models which increase the efficiency of proper matching and earn time to save lives. The existing methods for member selection pay much attention to the individual information to measure the individual performance of members, while few studies focus on the collaborative information to measure the collaborative performance between members. This paper aims to propose a two-stage method for member selection of an MET. In the first stage, knowledge rules are proposed to identify the valid candidates quickly. In the second stage, the individual information of members, the collaborative information between members, and the response time of EMS are all considered to build a three-objective 0-1 programming model. Due to its intractability, the model is solved by a non-dominated sorting genetic algorithm II. Liberia, now suffering the Ebola virus, is used as a backdrop for this study. A practical example followed by a computational simulation experiment is used to illustrate the applicability and the effectiveness of the proposed method.

Suggested Citation

  • Xi Chen & Zhiping Fan & Zhiwu Li & Xueliang Han & Xiao Zhang & Haochen Jia, 2015. "A two-stage method for member selection of emergency medical service," Journal of Combinatorial Optimization, Springer, vol. 30(4), pages 871-891, November.
    • Handle: RePEc:spr:jcomop:v:30:y:2015:i:4:d:10.1007_s10878-015-9856-z
    DOI: 10.1007/s10878-015-9856-z
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    References listed on IDEAS

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    5. Ling Gai & Zhiyue Peng & Jiming Zhang & Jiafu Zhang, 2021. "Emergency medical center location problem with people evacuation solved by extended TODIM and objective programming," Journal of Combinatorial Optimization, Springer, vol. 42(4), pages 1004-1029, November.
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    7. Xuerui Gao & Yanqin Bai & Qian Li, 0. "A sparse optimization problem with hybrid $$L_2{\text {-}}L_p$$L2-Lp regularization for application of magnetic resonance brain images," Journal of Combinatorial Optimization, Springer, vol. 0, pages 1-25.
    8. Ling Gai & Zhiyue Peng & Jiming Zhang & Jiafu Zhang, 0. "Emergency medical center location problem with people evacuation solved by extended TODIM and objective programming," Journal of Combinatorial Optimization, Springer, vol. 0, pages 1-26.

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