Design optimization of water distribution networks : real-world case study with penalty-free multi-objective genetic algorithm using pressure-driven simulation
Tanyimboh, Tiku T and Seyoum, Alemtsehay G (2020) Design optimization of water distribution networks : real-world case study with penalty-free multi-objective genetic algorithm using pressure-driven simulation. Water SA, 46 (3). pp. 465-475. ISSN 0378-4738 (https://doi.org/10.17159/wsa/2020.v46.i3.8657)
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Abstract
Water distribution systems are an integral part of the economic infrastructure of modern-day societies. However, previous research on the design optimization of water distribution systems generally involved few decision variables and consequently small solution spaces; piecemeal-solution methods based on pre-processing and search space reduction; and/or combinations of techniques working in concert. The present investigation was motivated by the desire to address the above-mentioned issues including those associated with the lack of high-performance computing (HPC) expertise and limited access in developing countries. More specifically, the article’s aims are, firstly, to solve a practical water distribution network design optimization problem and, secondly, to develop and demonstrate a generic multi-objective genetic algorithm capable of achieving optimal and near-optimal solutions on complex real-world design optimization problems reliably and quickly. A multi-objective genetic algorithm was developed that applies sustained and extensive exploration of the active constraint boundaries. The computational efficiency was demonstrated by the small fraction of 10-245 function evaluations relative to the size of the solution space. Highly competitive solutions were achieved consistently, including a new best solution. The water utility’s detailed distribution network model in EPANET 2 was used for the hydraulic simulations. Therefore, with some additional improvements, the optimization algorithm developed could assist practitioners in day-to-day planning and design.
ORCID iDs
Tanyimboh, Tiku T
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Item type: Article ID code: 77225 Dates: DateEvent28 July 2020Published15 June 2020AcceptedKeywords: generational distance, genetic algorithm, optimal sets, simulation, water distribution system, Environmental engineering, Engineering design, Applied Microbiology and Biotechnology, Water Science and Technology, Waste Management and Disposal, Management, Monitoring, Policy and Law Subjects: Technology > Engineering (General). Civil engineering (General) > Environmental engineering
Technology > Engineering (General). Civil engineering (General) > Engineering designDepartment: Faculty of Engineering > Civil and Environmental Engineering Depositing user: Pure Administrator Date deposited: 29 Jul 2021 14:47 Last modified: 15 Jun 2023 12:38 Related URLs: URI: https://strathprints.strath.ac.uk/id/eprint/77225