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Road network emergency accessibility planning after a major earthquake

Author

Listed:
  • Celso Satoshi Sakuraba

    (Universidade Federal de Sergipe
    Université de Technologie de Troyes)

  • Andréa Cynthia Santos

    (Université de Technologie de Troyes)

  • Christian Prins

    (Université de Technologie de Troyes)

  • Lucie Bouillot

    (SERTIT, Parc d’Innovation)

  • Arnaud Durand

    (SERTIT, Parc d’Innovation)

  • Bernard Allenbach

    (SERTIT, Parc d’Innovation)

Abstract

In the aftermath of disasters such as major earthquakes, several roads may be blocked by rubble and the population tends to search refugee in certain gathering points of the city. Road network accessibility becomes an important issue for logistic operations, specially on the first days after the quake, when the relief distribution is crucial for survival. This study focused on the Road Emergency Rehabilitation Problem, divided into the Road Network Accessibility Problem (RNAP) and the Work-troops Scheduling Problem (WSP). The first one consists in finding traversable paths for relief teams to reach the population, and the later generates a repairing schedule to improve access to refugee areas. The contributions of this study are two-fold: we present the process of transcribing satellite imagery data into graphs, and mathematical formulations for the RNAP and WSP, along with heuristics to solve the WSP. The proposed methods are able to handle large-scale graphs in an acceptable running time for real scenarios. They are tested on simulated instances and on the graph of Port-au-Prince, with more than 10,000 vertices and edges. The Port-au-Prince graph was generated from satellite images obtained by the International Charter “Space and Major Disasters” a few hours after the 2010 earthquake.

Suggested Citation

  • Celso Satoshi Sakuraba & Andréa Cynthia Santos & Christian Prins & Lucie Bouillot & Arnaud Durand & Bernard Allenbach, 2016. "Road network emergency accessibility planning after a major earthquake," EURO Journal on Computational Optimization, Springer;EURO - The Association of European Operational Research Societies, vol. 4(3), pages 381-402, September.
    • Handle: RePEc:spr:eurjco:v:4:y:2016:i:3:d:10.1007_s13675-016-0070-2
    DOI: 10.1007/s13675-016-0070-2
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    References listed on IDEAS

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    1. Tuzun Aksu, Dilek & Ozdamar, Linet, 2014. "A mathematical model for post-disaster road restoration: Enabling accessibility and evacuation," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 61(C), pages 56-67.
    2. Caunhye, Aakil M. & Nie, Xiaofeng & Pokharel, Shaligram, 2012. "Optimization models in emergency logistics: A literature review," Socio-Economic Planning Sciences, Elsevier, vol. 46(1), pages 4-13.
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    Cited by:

    1. Amadeu A. Coco & Christophe Duhamel & Andréa Cynthia Santos, 2020. "Modeling and solving the multi-period disruptions scheduling problem on urban networks," Annals of Operations Research, Springer, vol. 285(1), pages 427-443, February.
    2. 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).
    3. 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.

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