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Triage Scheduling Optimization for Mass Casualty and Disaster Response

Author

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  • Xiang Chu

    (School of Management Science and Engineering, Dalian University of Technology, Dalian 116024, P. R. China2Dalian Institute of Software and Services Outsourcing, 116024 Dalian, P. R. China)

  • Qiu-Yan Zhong

    (School of Management Science and Engineering, Dalian University of Technology, Dalian 116024, P. R. China)

  • Shahid G. Khokhar

    (School of Management Science and Engineering, Dalian University of Technology, Dalian 116024, P. R. China)

Abstract

This paper discusses casualty and medical group scheduling for disaster response in order to reduce casualities. First, triage levels and their stochastic transition, Markov Chain, are introduced to establish a function from treated time to probability of death. Then, job shop scheduling model and a genetic algorithm are designed. Finally, we performed a simulation experiment, partially using real data of 5.12 Wenchuan earthquakes for reference. The results show that the algorithm reduces number of mortalities stably and efficiently while considering disturbance events.

Suggested Citation

  • Xiang Chu & Qiu-Yan Zhong & Shahid G. Khokhar, 2015. "Triage Scheduling Optimization for Mass Casualty and Disaster Response," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 32(06), pages 1-20, December.
    • Handle: RePEc:wsi:apjorx:v:32:y:2015:i:06:n:s0217595915500414
    DOI: 10.1142/S0217595915500414
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    References listed on IDEAS

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    1. Ji-Bo Wang & Ming-Zheng Wang, 2013. "Makespan Minimization On Three-Machine Flow Shop With Deteriorating Jobs," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 30(06), pages 1-14.
    2. Van de Vonder, Stijn & Demeulemeester, Erik & Herroelen, Willy, 2008. "Proactive heuristic procedures for robust project scheduling: An experimental analysis," European Journal of Operational Research, Elsevier, vol. 189(3), pages 723-733, September.
    3. Wilson, Duncan T. & Hawe, Glenn I. & Coates, Graham & Crouch, Roger S., 2013. "A multi-objective combinatorial model of casualty processing in major incident response," European Journal of Operational Research, Elsevier, vol. 230(3), pages 643-655.
    4. Lambrechts, Olivier & Demeulemeester, Erik & Herroelen, Willy, 2008. "A tabu search procedure for developing robust predictive project schedules," International Journal of Production Economics, Elsevier, vol. 111(2), pages 493-508, February.
    5. S. Q. Liu & H. L. Ong, 2004. "Metaheuristics For The Mixed Shop Scheduling Problem," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 21(01), pages 97-115.
    6. Shisheng Li, 2011. "Scheduling Proportionally Deteriorating Jobs In Two-Machine Open Shop With A Non-Bottleneck Machine," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 28(05), pages 623-631.
    7. Herroelen, Willy & Leus, Roel, 2004. "The construction of stable project baseline schedules," European Journal of Operational Research, Elsevier, vol. 156(3), pages 550-565, August.
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    Cited by:

    1. Xiang Chu & QiuYan Zhong, 2015. "Post-earthquake allocation approach of medical rescue teams," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 79(3), pages 1809-1824, December.

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