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A MILP model and a heuristic algorithm for post-disaster connectivity problem with heterogeneous vehicles

Author

Listed:
  • İlknur Tükenmez

    (Industrial Engineering Department)

  • Tugba Saraç

    (Industrial Engineering Department)

  • Onur Kaya

    (Industrial Engineering Department)

Abstract

Throughout the response phase of the disaster, the speedy restoration of transportation by reconnecting the nodes where the connection is broken is absolutely critical for evacuating civilians, providing clear access to hospitals, and distributing aid. Following a disaster, some roads in a disaster area might be closed to transportation. In reality, some roads can be blocked due to debris, and some of roads can be blocked by collapsing. In this model, different types of road unblocking methods are included, and each road can only be opened to access by a vehicle suitable for that method. So, different types of vehicles may be needed to repair the roads depending on the type of damage. In addition, fast-built bridges built both on land and over water are also used if necessary following a disaster. In problems of this nature, it is essential to restore the roads to enable the complete connectivity of the network such that all nodes can be reached by one another. In addition, it is also critical for the speedy reach of critical nodes, such as hospitals, and emergency disaster centers. This study aims to reduce the maximum time for connection and minimize the total time in which to reach critical nodes. For this purpose, we developed a bi-objective mathematical model that considers the multiple vehicle types that can repair different types of damages. Since the problem is NP-hard, two heuristic methods were developed, and the numerical results were presented. It has been observed that the local search algorithm gives better results than the hybrid algorithm. Additionally, different scenario data was produced. Numbers of unconnected components from 3 to 10 are solved with heuristic algorithms for test data containing 80 and 250 nodes, and real-life data containing 223 nodes and 391 edges are solved with heuristic algorithms for the number of unconnected components 6, 9, 12, and 15.

Suggested Citation

  • İlknur Tükenmez & Tugba Saraç & Onur Kaya, 2024. "A MILP model and a heuristic algorithm for post-disaster connectivity problem with heterogeneous vehicles," Journal of Heuristics, Springer, vol. 30(5), pages 359-396, December.
    • Handle: RePEc:spr:joheur:v:30:y:2024:i:5:d:10.1007_s10732-024-09531-4
    DOI: 10.1007/s10732-024-09531-4
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    References listed on IDEAS

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    1. Kasin Ransikarbum & Scott J. Mason, 2016. "Multiple-objective analysis of integrated relief supply and network restoration in humanitarian logistics operations," International Journal of Production Research, Taylor & Francis Journals, vol. 54(1), pages 49-68, January.
    2. 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.
    3. 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.
    4. 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.
    5. Mahmoud Golabi & Seyed Mahdi Shavarani & Gokhan Izbirak, 2017. "An edge-based stochastic facility location problem in UAV-supported humanitarian relief logistics: a case study of Tehran earthquake," 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. 87(3), pages 1545-1565, July.
    6. Timothy Matisziw & Alan Murray & Tony Grubesic, 2010. "Strategic Network Restoration," Networks and Spatial Economics, Springer, vol. 10(3), pages 345-361, September.
    7. Tofighi, S. & Torabi, S.A. & Mansouri, S.A., 2016. "Humanitarian logistics network design under mixed uncertainty," European Journal of Operational Research, Elsevier, vol. 250(1), pages 239-250.
    8. Jose Escribano Macias & Nils Goldbeck & Pei-Yuan Hsu & Panagiotis Angeloudis & Washington Ochieng, 2020. "Endogenous stochastic optimisation for relief distribution assisted with unmanned aerial vehicles," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 42(4), pages 1089-1125, December.
    9. 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.
    10. 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.
    11. Ben-Tal, Aharon & Chung, Byung Do & Mandala, Supreet Reddy & Yao, Tao, 2011. "Robust optimization for emergency logistics planning: Risk mitigation in humanitarian relief supply chains," Transportation Research Part B: Methodological, Elsevier, vol. 45(8), pages 1177-1189, September.
    12. 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.
    13. 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.
    14. Kovacs, Gyöngyi & Moshtari, Mohammad, 2019. "A roadmap for higher research quality in humanitarian operations: A methodological perspective," European Journal of Operational Research, Elsevier, vol. 276(2), pages 395-408.
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