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Solution methodologies for debris removal in disaster response

Author

Listed:
  • Nihal Berktaş

    (Bilkent University)

  • Bahar Yetiş Kara

    (Bilkent University)

  • Oya Ekin Karaşan

    (Bilkent University)

Abstract

During the disaster response phase of the emergency relief, the aim is to reduce loss of human life by reaching disaster affected areas with relief items as soon as possible. Debris caused by the disaster blocks the roads and prevents emergency aid teams to access the disaster affected regions. Deciding which roads to clean to transport relief items is crucial to diminish the negative impact of a disaster on human health. Despite the significance of the problem during response phase, in the literature debris removal is mostly studied in the recovery or the reconstruction phases of a disaster. The aim of this study is providing solution methodologies for debris removal problem in the response phase in which effective and fast relief routing is of utmost importance. In particular, debris removal activities on certain blocked arcs have to be scheduled to reach a set of critical nodes such as schools and hospitals. To this end, two mathematical models are developed with different objectives. The first model aims to minimize the total time spent to reach all the critical nodes whereas the second minimizes the weighted sum of visiting times where weights indicate the priorities of critical nodes. Since obtaining solutions quickly is important in the early post-disaster, heuristic algorithms are also proposed. Two data sets belonging to Kartal and Bakırköy districts of İstanbul are used to test the mathematical models and heuristics.

Suggested Citation

  • 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.
    • Handle: RePEc:spr:eurjco:v:4:y:2016:i:3:d:10.1007_s13675-016-0063-1
    DOI: 10.1007/s13675-016-0063-1
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    7. Cheng, Cheng & Lu, Jia-Wei & Zhu, Rui & Xiao, Zuopeng & Costa, Alysson M. & Thompson, Russell G., 2022. "An integrated multi-objective model for disaster waste clean-up systems optimization," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 165(C).
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    10. Sayarshad, Hamid R. & Du, Xinpi & Gao, H. Oliver, 2020. "Dynamic post-disaster debris clearance problem with re-positioning of clearance equipment items under partially observable information," Transportation Research Part B: Methodological, Elsevier, vol. 138(C), pages 352-372.
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    15. 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.

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