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An online optimization approach to post-disaster road restoration

Author

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  • Akbari, Vahid
  • Shiri, Davood
  • Sibel Salman, F.

Abstract

Natural disasters impact transportation networks adversely and cause road sections to be damaged or blocked. The road network may even become disconnected, impeding accessibility between disaster-stricken areas and critical locations such as hospitals, relief aid depots and transportation hubs. In the immediate response phase, a set of blocked edges should be selected and restored to reconnect the transportation network. While locations of the disrupted roads can be identified using drone or satellite images, an accurate estimation of time to restore a road segment can be carried out only after expert observations on the field. In this article, we study a post-disaster road restoration problem modeled on an undirected edge-weighted graph with k blocked edges, where the unblocking time of a blocked edge is revealed online once the road restoration team visits an end-node of that blocked edge. The objective is to minimize the time at which the road network is reconnected. We first investigate the worst-case performance of online algorithms against offline optimal solutions by means of the competitive ratio. We prove that any online deterministic algorithm cannot achieve a competitive ratio better than 2k−1. We also provide an optimal online algorithm that is proven to achieve this lower bound. In addition, to achieve good performance on realistic instances, we implement an algorithm that solves a mixed integer programming model each time new information is revealed. Since model solution is prohibitively time-consuming, we also propose a novel polynomial time online algorithm. We compare these two algorithms with two other benchmark online algorithms on both Istanbul road network instances and several other city instances from the literature. Our experiments show that the proposed polynomial time online algorithm performs superior to the benchmark ones and obtains solutions close to the offline optimum on all the tested instances.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:transb:v:150:y:2021:i:c:p:1-25
    DOI: 10.1016/j.trb.2021.05.017
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    References listed on IDEAS

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    1. Aakil M. Caunhye & Nazli Yonca Aydin & H. Sebnem Duzgun, 2020. "Robust post-disaster route restoration," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 42(4), pages 1055-1087, December.
    2. 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.
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    4. Ransikarbum, Kasin & Mason, Scott J., 2016. "Goal programming-based post-disaster decision making for integrated relief distribution and early-stage network restoration," International Journal of Production Economics, Elsevier, vol. 182(C), pages 324-341.
    5. 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.
    6. 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.
    7. 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.
    8. Akbari, Vahid & Shiri, Davood, 2021. "Weighted online minimum latency problem with edge uncertainty," European Journal of Operational Research, Elsevier, vol. 295(1), pages 51-65.
    9. 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.
    10. Chung-Shou Liao & Yamming Huang, 2015. "Generalized Canadian traveller problems," Journal of Combinatorial Optimization, Springer, vol. 29(4), pages 701-712, May.
    11. Davood Shiri & F. Sibel Salman, 2019. "Competitive analysis of randomized online strategies for the multi-agent k-Canadian Traveler Problem," Journal of Combinatorial Optimization, Springer, vol. 37(3), pages 848-865, April.
    12. Davood Shiri & Vahid Akbari & F. Sibel Salman, 2020. "Online routing and scheduling of search-and-rescue teams," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 42(3), pages 755-784, September.
    13. Davood Shiri & F. Sibel Salman, 2017. "On the online multi-agent O–D k-Canadian Traveler Problem," Journal of Combinatorial Optimization, Springer, vol. 34(2), pages 453-461, August.
    14. 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.
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    16. 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.
    17. 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.
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    19. Davood Shiri & F. Sibel Salman, 2019. "On the randomized online strategies for the k-Canadian traveler problem," Journal of Combinatorial Optimization, Springer, vol. 38(1), pages 254-267, July.
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    22. Melih Çelik & Özlem Ergun & Pınar Keskinocak, 2015. "The Post-Disaster Debris Clearance Problem Under Incomplete Information," Operations Research, INFORMS, vol. 63(1), pages 65-85, February.
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    Cited by:

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    2. Shiri, Davood & Akbari, Vahid & Hassanzadeh, Ali, 2024. "The Capacitated Team Orienteering Problem: An online optimization framework with predictions of unknown accuracy," Transportation Research Part B: Methodological, Elsevier, vol. 185(C).
    3. 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.
    4. 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.
    5. 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).
    6. Jin, Zhongyi & Ng, Kam K.H. & Zhang, Chenliang & Liu, Wei & Zhang, Fangni & Xu, Gangyan, 2024. "A risk-averse distributionally robust optimisation approach for drone-supported relief facility location problem," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 186(C).
    7. 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).
    8. M. Ali Ülkü & James H. Bookbinder & Nam Yi Yun, 2024. "Leveraging Industry 4.0 Technologies for Sustainable Humanitarian Supply Chains: Evidence from the Extant Literature," Sustainability, MDPI, vol. 16(3), pages 1-26, February.

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