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Emergency Relief Routing Models for Injured Victims Considering Equity and Priority

Author

Listed:
  • Li Zhu

    (NUIST - Nanjing University of Information Science and Technology)

  • Yeming Gong

    (EM - EMLyon Business School)

  • Yishui Xu

    (NUIST - Nanjing University of Information Science and Technology)

  • Jun Gu

    (NUIST - Nanjing University of Information Science and Technology)

Abstract

In humanitarian aid, emergency relief routing optimization needs to consider equity and priority issues. Different from the general path selection optimization, this paper builds two models differentiated by considerations on the identical and diverse injured degrees, where the relative deprivation cost is proposed as one of the decision-making objectives to emphasize equity, and the in-transit tolerable suffering duration is employed as a type of time window constraint to highlight rescue priority. After proving the NP-hardness of our models, we design a meta-heuristic algorithm based on the ant colony optimization to accelerate the convergence speed, which is more efficient than the commonly-used genetic algorithm. Taking 2017 Houston Flood as a case, we find results by performing the experimental comparison and sensitivity analysis. First, our models have advantages in the fairness of human sufferings mitigation. Second, the role of the in-transit tolerable suffering time window cannot be ignored in humanitarian relief solutions. Various measures are encouraged to extend this type of time window for achieving better emergency relief. Finally, our proposed hybrid transportation strategy aiming at diverse injured degrees stably outperforms the separated strategy, both in operational cost control and psychological sufferings alleviation, especially when relief supplies are limited.

Suggested Citation

  • Li Zhu & Yeming Gong & Yishui Xu & Jun Gu, 2019. "Emergency Relief Routing Models for Injured Victims Considering Equity and Priority," Post-Print hal-02312250, HAL.
  • Handle: RePEc:hal:journl:hal-02312250
    DOI: 10.1007/s10479-018-3089-3
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    Citations

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    Cited by:

    1. Yichen Lu & Chao Yang & Jun Yang, 2022. "A multi-objective humanitarian pickup and delivery vehicle routing problem with drones," Annals of Operations Research, Springer, vol. 319(1), pages 291-353, December.
    2. Linlin Zhang & Na Cui, 2021. "Pre-Positioning Facility Location and Resource Allocation in Humanitarian Relief Operations Considering Deprivation Costs," Sustainability, MDPI, vol. 13(8), pages 1-26, April.
    3. Kamyabniya, Afshin & Noormohammadzadeh, Zohre & Sauré, Antoine & Patrick, Jonathan, 2021. "A robust integrated logistics model for age-based multi-group platelets in disaster relief operations," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 152(C).
    4. Surajit Bag & Shivam Gupta & Lincoln Wood, 2022. "Big data analytics in sustainable humanitarian supply chain: barriers and their interactions," Annals of Operations Research, Springer, vol. 319(1), pages 721-760, December.
    5. Wapee Manopiniwes & Takashi Irohara, 2021. "Optimization model for temporary depot problem in flood disaster response," 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. 105(2), pages 1743-1763, January.
    6. Rameshwar Dubey & Angappa Gunasekaran & Thanos Papadopoulos, 2019. "Disaster relief operations: past, present and future," Annals of Operations Research, Springer, vol. 283(1), pages 1-8, December.
    7. Rehan Asad & Muhammad Qaiser Saleem & Muhammad Salman Habib & Nadeem Ahmad Mufti & Shaker Mahmood Mayo, 2023. "Seismic risk assessment and hotspots prioritization: a developing country perspective," 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. 117(3), pages 2863-2901, July.

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