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Dynamic optimisation of preventative and corrective maintenance schedules for a large scale urban drainage system

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  • Chen, Yujie
  • Cowling, Peter
  • Polack, Fiona
  • Remde, Stephen
  • Mourdjis, Philip

Abstract

Gully pots or storm drains are located at the side of roads to provide drainage for surface water. We consider gully pot maintenance as a risk-driven maintenance problem. We explore policies for preventative and corrective maintenance actions, and build optimised routes for maintenance vehicles. Our solutions take the risk impact of gully pot failure and its failure behaviour into account, in the presence of factors such as location, season and current status. The aim is to determine a maintenance policy that can automatically adjust its scheduling strategy in line with changes in the local environment, to minimise the surface flooding risk due to clogged gully pots. We introduce a rolling planning strategy, solved by a hyper-heuristic method. Results show the behaviour and strength of the automated adjustment in a range of real-world scenarios.

Suggested Citation

  • Chen, Yujie & Cowling, Peter & Polack, Fiona & Remde, Stephen & Mourdjis, Philip, 2017. "Dynamic optimisation of preventative and corrective maintenance schedules for a large scale urban drainage system," European Journal of Operational Research, Elsevier, vol. 257(2), pages 494-510.
    • Handle: RePEc:eee:ejores:v:257:y:2017:i:2:p:494-510
    DOI: 10.1016/j.ejor.2016.07.027
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    Cited by:

    1. Jiun-Huei Jang, 2023. "Optimizing the Cleaning Strategies to Reduce the Flood Risk Increased by Gully Blockages," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 37(4), pages 1747-1763, March.
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    3. Drake, John H. & Kheiri, Ahmed & Özcan, Ender & Burke, Edmund K., 2020. "Recent advances in selection hyper-heuristics," European Journal of Operational Research, Elsevier, vol. 285(2), pages 405-428.
    4. 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.
    5. Li, Yulong & Zhang, Chi & Jia, Chuanzhou & Li, Xiaodong & Zhu, Yimin, 2019. "Joint optimization of workforce scheduling and routing for restoring a disrupted critical infrastructure," Reliability Engineering and System Safety, Elsevier, vol. 191(C).
    6. Sankaranarayanan, Sriram & Feijoo, Felipe & Siddiqui, Sauleh, 2018. "Sensitivity and covariance in stochastic complementarity problems with an application to North American natural gas markets," European Journal of Operational Research, Elsevier, vol. 268(1), pages 25-36.
    7. Lagos, Felipe & Pereira, Jordi, 2024. "Multi-armed bandit-based hyper-heuristics for combinatorial optimization problems," European Journal of Operational Research, Elsevier, vol. 312(1), pages 70-91.
    8. Xianlong Ge & Yuanzhi Jin & Long Zhang, 2023. "Genetic-based algorithms for cash-in-transit multi depot vehicle routing problems: economic and environmental optimization," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 25(1), pages 557-586, January.
    9. Yang, Zhe & Baraldi, Piero & Zio, Enrico, 2020. "A novel method for maintenance record clustering and its application to a case study of maintenance optimization," Reliability Engineering and System Safety, Elsevier, vol. 203(C).

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