IDEAS home Printed from https://ideas.repec.org/a/eee/ejores/v300y2022i2p689-712.html
   My bibliography  Save this article

Synchronizing victim evacuation and debris removal: A data-driven robust prediction approach

Author

Listed:
  • Nabavi, S.M.
  • Vahdani, Behnam
  • Nadjafi, B. Afshar
  • Adibi, M.A.

Abstract

This study introduces a new perspective in disaster management's response and post-disaster phases to synchronize multiple vehicles for victim evacuation and debris removal processes. A broad range of interrelated scheduling and routing operations and various synchronization aspects of heterogeneous vehicles are considered in this regard. A novel bi-objective mixed-integer programming model is presented, where the first objective function aims to minimize the total costs of the relief logistics network, and the second one minimizes the total operation times of vehicles. Moreover, due to extensive empirical and analytical errors, preliminary travel and service times are inexact and unreliable. Hence, a novel two-stage data-driven approach is rendered to predict reliable travel and service times. In the first stage, a new hybrid machine learning model is rendered to predict these times, and in the second stage, the distributionally robust optimization with φ-divergence is employed to surmount the unreliability of predicted times. A real case study is examined to illustrate the validity of the proposed model and solution approach. In addition, several simulation experiments are conducted to demonstrate the superiority of the proposed solution method in terms of robustness. Finally, the proposed framework can improve the planning by rendering meaningful insights concerning significant parameters' influence over the schedule and routing consequences.

Suggested Citation

  • Nabavi, S.M. & Vahdani, Behnam & Nadjafi, B. Afshar & Adibi, M.A., 2022. "Synchronizing victim evacuation and debris removal: A data-driven robust prediction approach," European Journal of Operational Research, Elsevier, vol. 300(2), pages 689-712.
  • Handle: RePEc:eee:ejores:v:300:y:2022:i:2:p:689-712
    DOI: 10.1016/j.ejor.2021.09.051
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0377221721008274
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.ejor.2021.09.051?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Aharon Ben-Tal & Dick den Hertog & Anja De Waegenaere & Bertrand Melenberg & Gijs Rennen, 2013. "Robust Solutions of Optimization Problems Affected by Uncertain Probabilities," Management Science, INFORMS, vol. 59(2), pages 341-357, April.
    2. Akbari, Vahid & Salman, F. Sibel, 2017. "Multi-vehicle synchronized arc routing problem to restore post-disaster network connectivity," European Journal of Operational Research, Elsevier, vol. 257(2), pages 625-640.
    3. Wex, Felix & Schryen, Guido & Feuerriegel, Stefan & Neumann, Dirk, 2014. "Emergency response in natural disaster management: Allocation and scheduling of rescue units," European Journal of Operational Research, Elsevier, vol. 235(3), pages 697-708.
    4. Vahdani, Behnam & Mohammadi, M., 2015. "A bi-objective interval-stochastic robust optimization model for designing closed loop supply chain network with multi-priority queuing system," International Journal of Production Economics, Elsevier, vol. 170(PA), pages 67-87.
    5. Saedinia, R. & Vahdani, Behnam & Etebari, F. & Afshar Nadjafi, B., 2019. "Robust gasoline closed loop supply chain design with redistricting, service sharing and intra-district service transfer," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 123(C), pages 121-141.
    6. Sabbaghtorkan, Monir & Batta, Rajan & He, Qing, 2020. "Prepositioning of assets and supplies in disaster operations management: Review and research gap identification," European Journal of Operational Research, Elsevier, vol. 284(1), pages 1-19.
    7. Morshedlou, Nazanin & González, Andrés D. & Barker, Kash, 2018. "Work crew routing problem for infrastructure network restoration," Transportation Research Part B: Methodological, Elsevier, vol. 118(C), pages 66-89.
    8. Shuanglin Li & Kok Lay Teo, 2019. "Post-disaster multi-period road network repair: work scheduling and relief logistics optimization," Annals of Operations Research, Springer, vol. 283(1), pages 1345-1385, December.
    9. Soares, Ricardo & Marques, Alexandra & Amorim, Pedro & Rasinmäki, Jussi, 2019. "Multiple vehicle synchronisation in a full truck-load pickup and delivery problem: A case-study in the biomass supply chain," European Journal of Operational Research, Elsevier, vol. 277(1), pages 174-194.
    10. D. D. Li & D. X. Yu & Z. J. Qu & S. H. Yu, 2020. "Feature Selection and Model Fusion Approach for Predicting Urban Macro Travel Time," Mathematical Problems in Engineering, Hindawi, vol. 2020, pages 1-13, June.
    11. Fatemeh Sabouhi & Ali Bozorgi-Amiri & Mohammad Moshref-Javadi & Mehdi Heydari, 2019. "An integrated routing and scheduling model for evacuation and commodity distribution in large-scale disaster relief operations: a case study," Annals of Operations Research, Springer, vol. 283(1), pages 643-677, December.
    12. Iloglu, Suzan & Albert, Laura A., 2018. "An integrated network design and scheduling problem for network recovery and emergency response," Operations Research Perspectives, Elsevier, vol. 5(C), pages 218-231.
    13. Ching-Hui Tang & Shangyao Yan & Chia-Wei Chang, 2009. "Short-term work team scheduling models for effective road repair and management," Transportation Planning and Technology, Taylor & Francis Journals, vol. 32(3), pages 289-311, April.
    14. Chengxi Liu & Yusak O. Susilo & Anders Karlström, 2017. "Weather variability and travel behaviour – what we know and what we do not know," Transport Reviews, Taylor & Francis Journals, vol. 37(6), pages 715-741, November.
    15. Robert Ward & Gary Wamsley & Aaron Schroeder & David B. Robins, 2000. "Network organizational development in the public sector: A case study of the federal emergency management administration (FEMA)," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 51(11), pages 1018-1032.
    16. Zhu, Ning & Fu, Chenyi & Ma, Shoufeng, 2018. "Data-driven distributionally robust optimization approach for reliable travel-time-information-gain-oriented traffic sensor location model," Transportation Research Part B: Methodological, Elsevier, vol. 113(C), pages 91-120.
    17. Moreno, Alfredo & Alem, Douglas & Gendreau, Michel & Munari, Pedro, 2020. "The heterogeneous multicrew scheduling and routing problem in road restoration," Transportation Research Part B: Methodological, Elsevier, vol. 141(C), pages 24-58.
    18. Nihal Berktaş & Bahar Yetiş Kara & Oya Ekin Karaşan, 2016. "Solution methodologies for debris removal in disaster response," EURO Journal on Computational Optimization, Springer;EURO - The Association of European Operational Research Societies, vol. 4(3), pages 403-445, September.
    19. David Todd & Hazel Todd, 2011. "Natural Disaster Response," World Bank Publications - Books, The World Bank Group, number 27353.
    20. Özdamar, Linet & Tüzün Aksu, Dilek & Ergüneş, Biket, 2014. "Coordinating debris cleanup operations in post disaster road networks," Socio-Economic Planning Sciences, Elsevier, vol. 48(4), pages 249-262.
    21. Vahdani, Behnam & Tavakkoli-Moghaddam, Reza & Modarres, Mohammad & Baboli, Armand, 2012. "Reliable design of a forward/reverse logistics network under uncertainty: A robust-M/M/c queuing model," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 48(6), pages 1152-1168.
    22. Dorota Mankowska & Frank Meisel & Christian Bierwirth, 2014. "The home health care routing and scheduling problem with interdependent services," Health Care Management Science, Springer, vol. 17(1), pages 15-30, March.
    23. Ulusan, Aybike & Ergun, Özlem, 2021. "Approximate dynamic programming for network recovery problems with stochastic demand," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 151(C).
    24. Akbari, Vahid & Shiri, Davood & Sibel Salman, F., 2021. "An online optimization approach to post-disaster road restoration," Transportation Research Part B: Methodological, Elsevier, vol. 150(C), pages 1-25.
    25. Juliette García-Alviz & Gina Galindo & Julián Arellana & Ruben Yie-Pinedo, 2021. "Planning road network restoration and relief distribution under heterogeneous road disruptions," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 43(4), pages 941-981, December.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Hosseini, Yaser & Mohammadi, Reza Karami & Yang, Tony Y., 2024. "A comprehensive approach in post-earthquake blockage prediction of urban road network and emergency resilience optimization," Reliability Engineering and System Safety, Elsevier, vol. 244(C).
    2. Vahdani, Behnam & Mohammadi, Mehrdad & Thevenin, Simon & Gendreau, Michel & Dolgui, Alexandre & Meyer, Patrick, 2023. "Fair-split distribution of multi-dose vaccines with prioritized age groups and dynamic demand: The case study of COVID-19," European Journal of Operational Research, Elsevier, vol. 310(3), pages 1249-1272.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Souza Almeida, Luana & Goerlandt, Floris & Pelot, Ronald, 2022. "Trends and gaps in the literature of road network repair and restoration in the context of disaster response operations," Socio-Economic Planning Sciences, Elsevier, vol. 84(C).
    2. Ajam, Meraj & Akbari, Vahid & Salman, F. Sibel, 2022. "Routing multiple work teams to minimize latency in post-disaster road network restoration," European Journal of Operational Research, Elsevier, vol. 300(1), pages 237-254.
    3. Moreno, Alfredo & Alem, Douglas & Gendreau, Michel & Munari, Pedro, 2020. "The heterogeneous multicrew scheduling and routing problem in road restoration," Transportation Research Part B: Methodological, Elsevier, vol. 141(C), pages 24-58.
    4. Hosseini, Yaser & Mohammadi, Reza Karami & Yang, Tony Y., 2024. "A comprehensive approach in post-earthquake blockage prediction of urban road network and emergency resilience optimization," Reliability Engineering and System Safety, Elsevier, vol. 244(C).
    5. Rodríguez-Espíndola, Oscar & Ahmadi, Hossein & Gastélum-Chavira, Diego & Ahumada-Valenzuela, Omar & Chowdhury, Soumyadeb & Dey, Prasanta Kumar & Albores, Pavel, 2023. "Humanitarian logistics optimization models: An investigation of decision-maker involvement and directions to promote implementation," Socio-Economic Planning Sciences, Elsevier, vol. 89(C).
    6. Shuanglin Li & Kok Lay Teo, 2019. "Post-disaster multi-period road network repair: work scheduling and relief logistics optimization," Annals of Operations Research, Springer, vol. 283(1), pages 1345-1385, December.
    7. Akbari, Vahid & Shiri, Davood & Sibel Salman, F., 2021. "An online optimization approach to post-disaster road restoration," Transportation Research Part B: Methodological, Elsevier, vol. 150(C), pages 1-25.
    8. Farzaneh, Mohammad Amin & Rezapour, Shabnam & Baghaian, Atefe & Amini, M. Hadi, 2023. "An integrative framework for coordination of damage assessment, road restoration, and relief distribution in disasters," Omega, Elsevier, vol. 115(C).
    9. Ajam, Meraj & Akbari, Vahid & Salman, F. Sibel, 2019. "Minimizing latency in post-disaster road clearance operations," European Journal of Operational Research, Elsevier, vol. 277(3), pages 1098-1112.
    10. Moreno, Alfredo & Munari, Pedro & Alem, Douglas, 2019. "A branch-and-Benders-cut algorithm for the Crew Scheduling and Routing Problem in road restoration," European Journal of Operational Research, Elsevier, vol. 275(1), pages 16-34.
    11. Vahdani, Behnam & Veysmoradi, D. & Mousavi, S.M. & Amiri, M., 2022. "Planning for relief distribution, victim evacuation, redistricting and service sharing under uncertainty," Socio-Economic Planning Sciences, Elsevier, vol. 80(C).
    12. Sanci, Ece & Daskin, Mark S., 2019. "Integrating location and network restoration decisions in relief networks under uncertainty," European Journal of Operational Research, Elsevier, vol. 279(2), pages 335-350.
    13. de Castro Pena, Guilherme & Santos, Andréa Cynthia & Prins, Christian, 2023. "Solving the integrated multi-period scheduling routing problem for cleaning debris in the aftermath of disasters," European Journal of Operational Research, Elsevier, vol. 306(1), pages 156-172.
    14. Juliette García-Alviz & Gina Galindo & Julián Arellana & Ruben Yie-Pinedo, 2021. "Planning road network restoration and relief distribution under heterogeneous road disruptions," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 43(4), pages 941-981, December.
    15. Eren Atsiz & Burcu Balcik & Dilek Gunnec & Busra Uydasoglu Sevindik, 2022. "A coordinated repair routing problem for post-disaster recovery of interdependent infrastructure networks," Annals of Operations Research, Springer, vol. 319(1), pages 41-71, December.
    16. Zhalechian, M. & Tavakkoli-Moghaddam, R. & Zahiri, B. & Mohammadi, M., 2016. "Sustainable design of a closed-loop location-routing-inventory supply chain network under mixed uncertainty," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 89(C), pages 182-214.
    17. Xu, Min & Ouyang, Min & Hong, Liu & Mao, Zijun & Xu, Xiaolin, 2022. "Resilience-driven repair sequencing decision under uncertainty for critical infrastructure systems," Reliability Engineering and System Safety, Elsevier, vol. 221(C).
    18. Zhang, Guowei & Zhu, Ning & Ma, Shoufeng & Xia, Jun, 2021. "Humanitarian relief network assessment using collaborative truck-and-drone system," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 152(C).
    19. Bowen Guo & Wei Zhan, 2023. "Research on Integrated Scheduling of Multi-Mode Emergency Rescue for Flooding in Chemical Parks," Sustainability, MDPI, vol. 15(4), pages 1-18, February.
    20. Bešinović, Nikola & Ferrari Nassar, Raphael & Szymula, Christopher, 2022. "Resilience assessment of railway networks: Combining infrastructure restoration and transport management," Reliability Engineering and System Safety, Elsevier, vol. 224(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:ejores:v:300:y:2022:i:2:p:689-712. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/eor .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.