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Joint optimization of maintenance planning and workforce routing for a geographically distributed networked infrastructure

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  • Chuanzhou Jia
  • Chi Zhang

Abstract

It is paramount to perform timely and appropriate maintenance actions on networked infrastructures, such as power transmission, transportation, telecommunications, and so forth, in order to ensure their reliability in satisfying the prescribed demand required by the economic development and social well-being of a society. For this purpose, the time of travelling between the components to be maintained needs to be considered, as the components of a real-world infrastructure are usually geographically widely distributed. To address this problem, we propose a holistic bi-objective optimization approach for the joint optimization of maintenance planning and workforce routing for a networked infrastructure, in order to determine a practical maintenance plan that can simultaneously maximize its reliability and minimize the incurred cost. To deal with the complexity of the proposed problem, we develop a Two-level Pareto Simulated Annealing algorithm to approximate the Pareto-optimal solutions of the proposed problem. Finally, two numerical examples are employed to illustrate the ability of the proposed approach in dealing with the maintenance optimization problem of a geographically distributed networked infrastructure.

Suggested Citation

  • Chuanzhou Jia & Chi Zhang, 2020. "Joint optimization of maintenance planning and workforce routing for a geographically distributed networked infrastructure," IISE Transactions, Taylor & Francis Journals, vol. 52(7), pages 732-750, July.
  • Handle: RePEc:taf:uiiexx:v:52:y:2020:i:7:p:732-750
    DOI: 10.1080/24725854.2019.1647478
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    Citations

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    Cited by:

    1. Agnieszka Blokus & Przemysław Dziula, 2021. "Relations of Imperfect Repairs to Critical Infrastructure Maintenance Costs," Sustainability, MDPI, vol. 13(9), pages 1-19, April.
    2. Si, Guojin & Xia, Tangbin & Li, Yaping & Wang, Dong & Chen, Zhen & Pan, Ershun & Xi, Lifeng, 2023. "Resource allocation and maintenance scheduling for distributed multi-center renewable energy systems considering dynamic scope division," Renewable Energy, Elsevier, vol. 217(C).
    3. Si, Guojin & Xia, Tangbin & Gebraeel, Nagi & Wang, Dong & Pan, Ershun & Xi, Lifeng, 2022. "A reliability-and-cost-based framework to optimize maintenance planning and diverse-skilled technician routing for geographically distributed systems," Reliability Engineering and System Safety, Elsevier, vol. 226(C).
    4. Jafar-Zanjani, Hamed & Zandieh, Mostafa & Sharifi, Mani, 2022. "Robust and resilient joint periodic maintenance planning and scheduling in a multi-factory network under uncertainty: A case study," Reliability Engineering and System Safety, Elsevier, vol. 217(C).
    5. Manco, Pasquale & Rinaldi, Marta & Caterino, Mario & Fera, Marcello & Macchiaroli, Roberto, 2022. "Maintenance management for geographically distributed assets: a criticality-based approach," Reliability Engineering and System Safety, Elsevier, vol. 218(PB).
    6. 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).
    7. Urbani, Michele & Brunelli, Matteo & Punkka, Antti, 2023. "An approach for bi-objective maintenance scheduling on a networked system with limited resources," European Journal of Operational Research, Elsevier, vol. 305(1), pages 101-113.
    8. Akl, Amany M. & El Sawah, Sondoss & Chakrabortty, Ripon K. & Turan, Hasan Hüseyin, 2022. "A Joint Optimization of Strategic Workforce Planning and Preventive Maintenance Scheduling: A Simulation–Optimization Approach," Reliability Engineering and System Safety, Elsevier, vol. 219(C).

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