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Article

An Enhanced Multi-Objective Particle Swarm Optimization in Water Distribution Systems Design

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Environmental Engineering Department, Egypt-Japan University of Science and Technology (E-JUST), New Borg El Arab City, Alexandria 21934, Egypt
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Irrigation Engineering and Hydraulics Department, Alexandria University, Alexandria 11432, Egypt
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Electronic Materials Researches Department, Advanced Technology and New Materials Research Institute, City of Scientific Research and Technological Applications (SRTA-City), New Borg El Arab City, Alexandria 21934, Egypt
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Computer Science and Engineering Department, E-JUST, New Borg El Arab City, Alexandria 21934, Egypt
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Computer and Systems Engineering Department, Alexandria University, Alexandria 11432, Egypt
*
Author to whom correspondence should be addressed.
Academic Editors: Mariacrocetta Sambito and Gabriele Freni
Water 2021, 13(10), 1334; https://doi.org/10.3390/w13101334
Received: 8 April 2021 / Revised: 4 May 2021 / Accepted: 6 May 2021 / Published: 11 May 2021
(This article belongs to the Special Issue Urban Water Networks Modelling and Monitoring)
The scarcity of water resources nowadays lays stress on researchers to develop strategies aiming at making the best benefit of the currently available resources. One of these strategies is ensuring that reliable and near-optimum designs of water distribution systems (WDSs) are achieved. Designing WDSs is a discrete combinatorial NP-hard optimization problem, and its complexity increases when more objectives are added. Among the many existing evolutionary algorithms, a new hybrid fast-convergent multi-objective particle swarm optimization (MOPSO) algorithm is developed to increase the convergence and diversity rates of the resulted non-dominated solutions in terms of network capital cost and reliability using a minimized computational budget. Several strategies are introduced to the developed algorithm, which are self-adaptive PSO parameters, regeneration-on-collision, adaptive population size, and using hypervolume quality for selecting repository members. A local search method is also coupled to both the original MOPSO algorithm and the newly developed one. Both algorithms are applied to medium and large benchmark problems. The results of the new algorithm coupled with the local search are superior to that of the original algorithm in terms of different performance metrics in the medium-sized network. In contrast, the new algorithm without the local search performed better in the large network. View Full-Text
Keywords: multi-objective algorithms; network resilience; particle swarm optimization; water distribution systems multi-objective algorithms; network resilience; particle swarm optimization; water distribution systems
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MDPI and ACS Style

Torkomany, M.R.; Hassan, H.S.; Shoukry, A.; Abdelrazek, A.M.; Elkholy, M. An Enhanced Multi-Objective Particle Swarm Optimization in Water Distribution Systems Design. Water 2021, 13, 1334. https://doi.org/10.3390/w13101334

AMA Style

Torkomany MR, Hassan HS, Shoukry A, Abdelrazek AM, Elkholy M. An Enhanced Multi-Objective Particle Swarm Optimization in Water Distribution Systems Design. Water. 2021; 13(10):1334. https://doi.org/10.3390/w13101334

Chicago/Turabian Style

Torkomany, Mohamed R., Hassan S. Hassan, Amin Shoukry, Ahmed M. Abdelrazek, and Mohamed Elkholy. 2021. "An Enhanced Multi-Objective Particle Swarm Optimization in Water Distribution Systems Design" Water 13, no. 10: 1334. https://doi.org/10.3390/w13101334

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