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A branch-and-Benders-cut algorithm for the Crew Scheduling and Routing Problem in road restoration

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  • Moreno, Alfredo
  • Munari, Pedro
  • Alem, Douglas

Abstract

Extreme events such as disasters cause partial or total disruption of basic services such as water, energy, communication and transportation. In particular, roads can be damaged or blocked by debris, thereby obstructing access to certain affected areas. Thus, restoration of the damaged roads is necessary to evacuate victims and distribute emergency commodities to relief centers or affected areas. The Crew Scheduling and Routing Problem (CSRP) addresses decisions in post-disaster situations with the aim of minimizing the time that affected areas remain inaccessible. The integration of crew scheduling and routing decisions makes this problem too complicated to be effectively solved for practical instances using mixed integer programming (MIP) formulations recently proposed in the literature. Therefore, we propose a branch-and-Benders-cut (BBC) algorithm that decomposes the integrated problem into a master problem (MP) with scheduling decisions and subproblems with routing decisions. Computational tests based on instances from the literature show that the proposed exact method improves the results of MIP formulations and other exact and metaheuristic methods proposed in literature. The BBC algorithm provides feasible solutions and optimality gaps for instances that thus far have not been possible to solve by exact methods in the literature.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:ejores:v:275:y:2019:i:1:p:16-34
    DOI: 10.1016/j.ejor.2018.11.004
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    2. Sakineh Lakzaei & Donya Rahmani & Babak Mohamadpour Tosarkani & Sepideh Nasiri, 2023. "Integrated optimal scheduling and routing of repair crew and relief vehicles after disaster: a novel hybrid solution approach," Annals of Operations Research, Springer, vol. 328(2), pages 1495-1522, September.
    3. 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.
    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. 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.
    7. 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.
    8. 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.
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