Optimal cost design of water distribution networks using a decomposition approach

Ho Min Lee, Do Guen Yoo, Ali Sadollah, Joong Hoon Kim

    Research output: Contribution to journalArticlepeer-review

    20 Citations (Scopus)

    Abstract

    Water distribution network decomposition, which is an engineering approach, is adopted to increase the efficiency of obtaining the optimal cost design of a water distribution network using an optimization algorithm. This study applied the source tracing tool in EPANET, which is a hydraulic and water quality analysis model, to the decomposition of a network to improve the efficiency of the optimal design process. The proposed approach was tested by carrying out the optimal cost design of two water distribution networks, and the results were compared with other optimal cost designs derived from previously proposed optimization algorithms. The proposed decomposition approach using the source tracing technique enables the efficient decomposition of an actual large-scale network, and the results can be combined with the optimal cost design process using an optimization algorithm. This proves that the final design in this study is better than those obtained with other previously proposed optimization algorithms.

    Original languageEnglish
    Pages (from-to)2141-2156
    Number of pages16
    JournalEngineering Optimization
    Volume48
    Issue number12
    DOIs
    Publication statusPublished - 2016 Dec 1

    Bibliographical note

    Funding Information:
    This work was supported by a National Research Foundation of Korean (NRF) grant funded by the Korean government (MSIP) [NRF-2013R1A2A1A01013886].

    Publisher Copyright:
    © 2016 Informa UK Limited, trading as Taylor & Francis Group.

    Keywords

    • decomposition approach
    • harmony search algorithm
    • optimal cost design
    • source tracing
    • water distribution network

    ASJC Scopus subject areas

    • Computer Science Applications
    • Control and Optimization
    • Management Science and Operations Research
    • Industrial and Manufacturing Engineering
    • Applied Mathematics

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