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Applications of network analysis and multi-objective genetic algorithm for selecting optimal water quality sensor locations in water distribution networks

KSCE Journal of Civil Engineering volume 19, pages 2333–2344 (2015)Cite this article

Abstract

In this study, optimal water quality sensor placement is performed based on the sensitivity of flow direction under different water demands for detecting accidental water quality contamination. First, Betweenness Centrality (BC), a network analysis method, is used for determining optimal locations considering a network’s connectivity. Second, sensor locations are optimized for minimizing the contaminant intrusion detection time using the travel time matrix and the Multi-Objective Genetic Algorithm (MOGA). These methods were applied to two water distribution networks. It was found that the BC method generates optimal locations close to the water sources and the water main, whereas the MOGA-based method generates optimal sensor locations far away from the sources. These results support the following conclusions. First, the installation priority of gauges can be determined with a more objective standard using the aforementioned two methods. Second, given specific objectives, the two models can be used as alternative decision-making tools for sensor installation.

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Authors and Affiliations

  1. School of Civil, Environmental and Architectural Engineering, Korea University, Seoul, 136-713, Korea

    Do Guen Yoo, Ali Sadollah & Joong Hoon Kim

  2. Dept. of Civil Engineering, Hoseo University, Asan, 336-795, Korea

    Gunhui Chung

Authors
  1. Do Guen Yoo
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  2. Gunhui Chung
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  3. Ali Sadollah
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  4. Joong Hoon Kim
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Correspondence to Joong Hoon Kim.

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Yoo, D.G., Chung, G., Sadollah, A. et al. Applications of network analysis and multi-objective genetic algorithm for selecting optimal water quality sensor locations in water distribution networks. KSCE J Civ Eng 19, 2333–2344 (2015). https://doi.org/10.1007/s12205-015-0273-8

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  • DOI: https://doi.org/10.1007/s12205-015-0273-8

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