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Work crew routing problem for infrastructure network restoration

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  • Morshedlou, Nazanin
  • González, Andrés D.
  • Barker, Kash

Abstract

This paper introduces a synchronized routing problem for planning and scheduling restorative efforts for infrastructure networks in the aftermath of a disruptive event. In this problem, a set of restoration crews are dispatched from depots to a road network to restore the disrupted infrastructure network. Two mathematical formulations are presented to scheduling and sequencing disrupted network components to restoration crews and route the crews towards disrupted components to maximize network resilience progress in any given time horizon. In the first formulation, the number of restoration crews assigned to each disrupted component, the arrival time of each assigned crew to each disrupted component and consequently the restoration rate associated with each disrupted component are considered as variables to increase the flexibility of the model in the presence of different disruptive events. Along with the contributions applies in the first formulation, in the second formulation, each disrupted component can be partially active during its restoration process. To find the coordinated routes, we propose a relaxed mixed integer program as well as a set of valid inequalities which relates the planning and scheduling efforts to decision makers policies. The integration of the relaxed formulation and valid inequalities results in a lower bound for the original formulations. We further introduce a feasibility algorithm to derive a strong initial solution for the routing restorative capacity problem. Computational results on gas, water, and electric power infrastructure network instances from Shelby County, TN data, demonstrates both the effectiveness of the proposed model formulation, in solving small to medium scale problems, the strength of the initial solution procedure, especially for large scale problems.

Suggested Citation

  • 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.
  • Handle: RePEc:eee:transb:v:118:y:2018:i:c:p:66-89
    DOI: 10.1016/j.trb.2018.10.001
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    5. Eren Atsiz & Burcu Balcik & Dilek Gunnec & Busra Uydasoglu Sevindik, 2022. "A coordinated repair routing problem for post-disaster recovery of interdependent infrastructure networks," Annals of Operations Research, Springer, vol. 319(1), pages 41-71, December.
    6. Ghaneshvar Ramineni & Nafiseh Ghorbani-Renani & Kash Barker & Andrés D. González & Talayeh Razzaghi & Sridhar Radhakrishnan, 2023. "Machine learning approaches to modeling interdependent network restoration time," Environment Systems and Decisions, Springer, vol. 43(1), pages 22-35, March.
    7. Ghorbani-Renani, Nafiseh & González, Andrés D. & Barker, Kash & Morshedlou, Nazanin, 2020. "Protection-interdiction-restoration: Tri-level optimization for enhancing interdependent network resilience," Reliability Engineering and System Safety, Elsevier, vol. 199(C).
    8. 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.
    9. 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.
    10. Dirk Briskorn & Alf Kimms & Denis Olschok, 2020. "Simultaneous planning for disaster road clearance and distribution of relief goods: a basic model and an exact solution method," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 42(3), pages 591-619, September.
    11. Hosseini, Seyedmohsen & Ivanov, Dmitry & Dolgui, Alexandre, 2019. "Review of quantitative methods for supply chain resilience analysis," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 125(C), pages 285-307.
    12. Kotsofana, T., 2013. "Informational economy: specific features and challenges of monopolization," Annals of marketing-mba, Department of Marketing, Marketing MBA (RSconsult), vol. 3, November.
    13. Bulina, A., 2013. "Transformation of institutions in the new economy," Annals of marketing-mba, Department of Marketing, Marketing MBA (RSconsult), vol. 3, November.
    14. Iloglu, Suzan & Albert, Laura A., 2020. "A maximal multiple coverage and network restoration problem for disaster recovery," Operations Research Perspectives, Elsevier, vol. 7(C).
    15. Maureen S. Golan & Laura H. Jernegan & Igor Linkov, 2020. "Trends and applications of resilience analytics in supply chain modeling: systematic literature review in the context of the COVID-19 pandemic," Environment Systems and Decisions, Springer, vol. 40(2), pages 222-243, June.
    16. 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).
    17. Jia, Chuanzhou & Zhang, Chi & Li, Yan-Fu & Li, Quan-Lin, 2023. "Joint pre- and post-disaster planning to enhance the resilience of critical infrastructures," Reliability Engineering and System Safety, Elsevier, vol. 231(C).
    18. Tiong, Achara & Vergara, Hector A., 2023. "Evaluation of network expansion decisions for resilient interdependent critical infrastructures with different topologies," International Journal of Critical Infrastructure Protection, Elsevier, vol. 42(C).
    19. Hannah Lobban & Yasser Almoghathawi & Nazanin Morshedlou & Kash Barker, 2021. "Community vulnerability perspective on robust protection planning in interdependent infrastructure networks," Journal of Risk and Reliability, , vol. 235(5), pages 798-813, October.
    20. Tiong, Achara & Vergara, Hector A., 2023. "A two-stage stochastic multi-objective resilience optimization model for network expansion of interdependent power–water networks under disruption," International Journal of Critical Infrastructure Protection, Elsevier, vol. 40(C).
    21. Babicheva E.E., 2015. "New Economy: Approaches, Features, Social Sphere Development," Annals of marketing-mba, Department of Marketing, Marketing MBA (RSconsult), vol. 2, May.
    22. Chesnokova, Maria, 2012. "Cross-cultural management: peculiarities of business cultures and communication problems," Annals of marketing-mba, Department of Marketing, Marketing MBA (RSconsult), vol. 3, November.
    23. Han, Lin & Zhao, Xudong & Chen, Zhilong & Gong, Huadong & Hou, Benwei, 2021. "Assessing resilience of urban lifeline networks to intentional attacks," Reliability Engineering and System Safety, Elsevier, vol. 207(C).
    24. 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.
    25. Garay-Sianca, Aniela & Nurre Pinkley, Sarah G., 2021. "Interdependent integrated network design and scheduling problems with movement of machines," European Journal of Operational Research, Elsevier, vol. 289(1), pages 297-327.

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