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Possibilistic scheduling routing for short-notice bushfire emergency evacuation under uncertainties: An Australian case study

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  • Shahparvari, Shahrooz
  • Abbasi, Babak
  • Chhetri, Prem

Abstract

This paper aims to develop a capacitated vehicle routing solution to evacuate short-notice evacuees with time windows and disruption risks under uncertainties during a bushfire. A heuristic solution technique is applied to solve the triangular possibilistic model to optimise emergency delivery service. The effectiveness of the proposed algorithm is evaluated by comparing it with a designed genetic algorithm on sets of 20 numerical examples. The model is then applied to the real case study of 2009 Black Saturday bushfires in Victoria, Australia. The results show that it is possible to transfer the last-minute evacuees during the Black Saturday bushfires under the hard time window constraint. Network disruptions however have impact on resource utilisation. The modelling outputs will be useful in the development of emergency plans and evacuation strategies to enhance rapid response to last-minute evacuation in a bushfire emergency.

Suggested Citation

  • Shahparvari, Shahrooz & Abbasi, Babak & Chhetri, Prem, 2017. "Possibilistic scheduling routing for short-notice bushfire emergency evacuation under uncertainties: An Australian case study," Omega, Elsevier, vol. 72(C), pages 96-117.
  • Handle: RePEc:eee:jomega:v:72:y:2017:i:c:p:96-117
    DOI: 10.1016/j.omega.2016.11.007
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    Cited by:

    1. Afkham, Maryam & Ramezanian, Reza & Shahparvari, Shahrooz, 2022. "Balancing traffic flow in the congested mass self-evacuation dynamic network under tight preparation budget: An Australian bushfire practice," Omega, Elsevier, vol. 111(C).
    2. Ghazaleh Ahmadi & Reza Tavakkoli-Moghaddam & Armand Baboli & Mehdi Najafi, 2022. "A decision support model for robust allocation and routing of search and rescue resources after earthquake: a case study," Operational Research, Springer, vol. 22(2), pages 1039-1081, April.
    3. Yuanyuan Feng & Yi Cao & Shuanghua Yang & Lili Yang & Tangjian Wei, 2023. "A two-step sub-optimal algorithm for bus evacuation planning," Operational Research, Springer, vol. 23(2), pages 1-35, June.
    4. Shahparvari, Shahrooz & Abbasi, Babak, 2017. "Robust stochastic vehicle routing and scheduling for bushfire emergency evacuation: An Australian case study," Transportation Research Part A: Policy and Practice, Elsevier, vol. 104(C), pages 32-49.
    5. Bashiri, Mahdi & Nikzad, Erfaneh & Eberhard, Andrew & Hearne, John & Oliveira, Fabricio, 2021. "A two stage stochastic programming for asset protection routing and a solution algorithm based on the Progressive Hedging algorithm," Omega, Elsevier, vol. 104(C).
    6. Schultz, Michael & Soolaki, Majid & Salari, Mostafa & Bakhshian, Elnaz, 2023. "A combined optimization–simulation approach for modified outside-in boarding under COVID-19 regulations including limited baggage compartment capacities," Journal of Air Transport Management, Elsevier, vol. 106(C).
    7. Inmaculada Flores & M. Teresa Ortuño & Gregorio Tirado & Begoña Vitoriano, 2020. "Supported Evacuation for Disaster Relief through Lexicographic Goal Programming," Mathematics, MDPI, vol. 8(4), pages 1-20, April.
    8. Esposito Amideo, A. & Scaparra, M.P. & Kotiadis, K., 2019. "Optimising shelter location and evacuation routing operations: The critical issues," European Journal of Operational Research, Elsevier, vol. 279(2), pages 279-295.
    9. Wang, Weiqiao & Yang, Kai & Yang, Lixing & Gao, Ziyou, 2023. "Distributionally robust chance-constrained programming for multi-period emergency resource allocation and vehicle routing in disaster response operations," Omega, Elsevier, vol. 120(C).

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