An Enhanced Multi-Objective Particle Swarm Optimization in Water Distribution Systems Design
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 WD...
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-05-01
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| Series: | Water |
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| Online Access: | https://www.mdpi.com/2073-4441/13/10/1334 |
| _version_ | 1797534588864561152 |
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| author | Mohamed R. Torkomany Hassan Shokry Hassan Amin Shoukry Ahmed M. Abdelrazek Mohamed Elkholy |
| author_facet | Mohamed R. Torkomany Hassan Shokry Hassan Amin Shoukry Ahmed M. Abdelrazek Mohamed Elkholy |
| author_sort | Mohamed R. Torkomany |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-10T11:31:40Z |
| format | Article |
| id | doaj.art-62d9adb52bcc470f830c190b29840642 |
| institution | Directory Open Access Journal |
| issn | 2073-4441 |
| language | English |
| last_indexed | 2024-03-10T11:31:40Z |
| publishDate | 2021-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Water |
| spelling | doaj.art-62d9adb52bcc470f830c190b298406422023-11-21T19:10:20ZengMDPI AGWater2073-44412021-05-011310133410.3390/w13101334An Enhanced Multi-Objective Particle Swarm Optimization in Water Distribution Systems DesignMohamed R. Torkomany0Hassan Shokry Hassan1Amin Shoukry2Ahmed M. Abdelrazek3Mohamed Elkholy4Environmental Engineering Department, Egypt-Japan University of Science and Technology (E-JUST), New Borg El Arab City, Alexandria 21934, EgyptEnvironmental Engineering Department, Egypt-Japan University of Science and Technology (E-JUST), New Borg El Arab City, Alexandria 21934, EgyptComputer Science and Engineering Department, E-JUST, New Borg El Arab City, Alexandria 21934, EgyptIrrigation Engineering and Hydraulics Department, Alexandria University, Alexandria 11432, EgyptIrrigation Engineering and Hydraulics Department, Alexandria University, Alexandria 11432, EgyptThe 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.https://www.mdpi.com/2073-4441/13/10/1334multi-objective algorithmsnetwork resilienceparticle swarm optimizationwater distribution systems |
| spellingShingle | Mohamed R. Torkomany Hassan Shokry Hassan Amin Shoukry Ahmed M. Abdelrazek Mohamed Elkholy An Enhanced Multi-Objective Particle Swarm Optimization in Water Distribution Systems Design Water multi-objective algorithms network resilience particle swarm optimization water distribution systems |
| title | An Enhanced Multi-Objective Particle Swarm Optimization in Water Distribution Systems Design |
| title_full | An Enhanced Multi-Objective Particle Swarm Optimization in Water Distribution Systems Design |
| title_fullStr | An Enhanced Multi-Objective Particle Swarm Optimization in Water Distribution Systems Design |
| title_full_unstemmed | An Enhanced Multi-Objective Particle Swarm Optimization in Water Distribution Systems Design |
| title_short | An Enhanced Multi-Objective Particle Swarm Optimization in Water Distribution Systems Design |
| title_sort | enhanced multi objective particle swarm optimization in water distribution systems design |
| topic | multi-objective algorithms network resilience particle swarm optimization water distribution systems |
| url | https://www.mdpi.com/2073-4441/13/10/1334 |
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