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Optimal coverage-based placement of static leak detection devices for pipeline water supply networks

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  • Blanco, Víctor
  • Martínez-Antón, Miguel

Abstract

In this paper, we provide a mathematical optimization-based framework to determine the location of leak detection devices along a network. Assuming that the devices are endowed with a known coverage area, we analyze two different models. The first model aims to minimize the number of devices to be located in order to (fully or partially) cover the volume of the network. In the second model, the number of devices is given, and the goal is to locate them to provide a coverage volume as broad as possible. Unlike other approaches in the literature, in our models, it is not assumed that the devices are located on the network (nodes or edges) but in the whole space and that the different segments in the networks may be partially covered, which allows for more flexible coverage. We also derive a method to construct initial solutions as well as a math-heuristic approach for solving the problem for larger instances. We report the results of a series of experiments on real-world water supply pipeline networks, supporting the validity of our models.

Suggested Citation

  • Blanco, Víctor & Martínez-Antón, Miguel, 2024. "Optimal coverage-based placement of static leak detection devices for pipeline water supply networks," Omega, Elsevier, vol. 122(C).
    • Handle: RePEc:eee:jomega:v:122:y:2024:i:c:s0305048323001202
    DOI: 10.1016/j.omega.2023.102956
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    References listed on IDEAS

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    1. Seckler, David & Amarasinghe, Upali A. & Molden, David J. & de Silva, Radhika & Barker, Randolph, 1998. "World water demand and supply, 1990 to 2025: scenarios and issues," IWMI Research Reports 61108, International Water Management Institute.
    2. Berman, Oded & Wang, Jiamin, 2011. "The minmax regret gradual covering location problem on a network with incomplete information of demand weights," European Journal of Operational Research, Elsevier, vol. 208(3), pages 233-238, February.
    3. Blanquero, Rafael & Carrizosa, Emilio & G.-Tóth, Boglárka, 2016. "Maximal Covering Location Problems on networks with regional demand," Omega, Elsevier, vol. 64(C), pages 77-85.
    4. Blanco, Víctor & González, Gabriel & Hinojosa, Yolanda & Ponce, Diego & Pozo, Miguel A. & Puerto, Justo, 2022. "Network flow based approaches for the pipelines routing problem in naval design," Omega, Elsevier, vol. 111(C).
    5. Victor Blanco & Justo Puerto & Safae El Haj Ben Ali, 2014. "Revisiting several problems and algorithms in continuous location with $$\ell _\tau $$ ℓ τ norms," Computational Optimization and Applications, Springer, vol. 58(3), pages 563-595, July.
    6. Murray, Alan T., 2021. "Contemporary optimization application through geographic information systems," Omega, Elsevier, vol. 99(C).
    7. Pelegrín, Mercedes & Xu, Liding, 2023. "Continuous covering on networks: Improved mixed integer programming formulations," Omega, Elsevier, vol. 117(C).
    8. Tedeschi, Danilo & Andretta, Marina, 2021. "New exact algorithms for planar maximum covering location by ellipses problems," European Journal of Operational Research, Elsevier, vol. 291(1), pages 114-127.
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    Cited by:

    1. Otto, Alena & Tilk, Christian, 2024. "Intelligent design of sensor networks for data-driven sensor maintenance at railways," Omega, Elsevier, vol. 127(C).

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