Optimization of water distribution network by genetic algorithm with EPANET-Python Toolkit
Water distribution systems (WDS) are essential for supplying water to urban and rural areas in an effective and consistent manner. This WDS operation may have a substantial effect on the environment and the sustainable development of cities in the future because of the substantial quantity of energy...
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| Vydáno v: | Journal of Earth System Science Ročník 134; číslo 4; s. 205 |
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| Hlavní autoři: | , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
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Bangalore
Springer Nature B.V
01.12.2025
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| ISSN: | 0973-774X, 0253-4126, 0973-774X |
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| Abstract | Water distribution systems (WDS) are essential for supplying water to urban and rural areas in an effective and consistent manner. This WDS operation may have a substantial effect on the environment and the sustainable development of cities in the future because of the substantial quantity of energy that WDSs consume over the course of their lives. To improve the quality of life and to maintain the sustainability of nature, optimization of the water distribution network (WDN) is essential and also crucial to guarantee the accessibility of safe drinking water to homes, businesses, industries, and public facilities. To provide optimal or nearly optimal solutions for large-scale and complicated WDS networks, the genetic algorithm (GA) is used to efficiently search across the enormous solution space. The optimization of pipe diameter is obtained with respect to total network cost by combining GA with the EPANET-Python Toolkit for the Benchmark Network (Hanoi Network) which is for validation purpose and later Real-world Network (Koodlahalli Network) which is made of High-Density Polyethylene (HDPE) pipe and cost of pipes in the network is reduced from Rs. 775989.42 to Rs. 690540.27, around (11%) has been reduced with minimum pressure of 7 m. |
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| AbstractList | Water distribution systems (WDS) are essential for supplying water to urban and rural areas in an effective and consistent manner. This WDS operation may have a substantial effect on the environment and the sustainable development of cities in the future because of the substantial quantity of energy that WDSs consume over the course of their lives. To improve the quality of life and to maintain the sustainability of nature, optimization of the water distribution network (WDN) is essential and also crucial to guarantee the accessibility of safe drinking water to homes, businesses, industries, and public facilities. To provide optimal or nearly optimal solutions for large-scale and complicated WDS networks, the genetic algorithm (GA) is used to efficiently search across the enormous solution space. The optimization of pipe diameter is obtained with respect to total network cost by combining GA with the EPANET-Python Toolkit for the Benchmark Network (Hanoi Network) which is for validation purpose and later Real-world Network (Koodlahalli Network) which is made of High-Density Polyethylene (HDPE) pipe and cost of pipes in the network is reduced from Rs. 775989.42 to Rs. 690540.27, around (11%) has been reduced with minimum pressure of 7 m. |
| ArticleNumber | 205 |
| Author | Pavansimha, M N Yusuf Javeed |
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| Cites_doi | 10.1007/s11269-017-1577-x 10.1061/(ASCE)0887-3801(1987)1:2(128) 10.22126/arww.2020.5061.1159 10.1029/WR013i006p00885 10.1061/(ASCE)0733-9496(2010)136:2(279) 10.1061/(ASCE)0733-9496(2004)130:1(73) 10.3390/w10030307 10.1016/j.jenvman.2018.08.054 10.14500/aro.10635 10.1080/03052150701503611 10.1016/j.scs.2023.104844 10.1007/s11269-005-9001-3 10.1109/ACCESS.2021.3052032 10.1080/15730620600855928 10.1061/40569(2001)378 10.1061/(ASCE)0733-9496(2003)129:3(200) 10.1061/(ASCE)0733-9496(1994)120:4(423) 10.1061/(ASCE)WR.1943-5452.0000515 10.1061/(ASCE)0733-9496(2003)129:3(210) |
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| References | MM Eusuff (2651_CR8) 2003; 129 J Marques (2651_CR25) 2018; 226 T Devi Prasad (2651_CR7) 2004; 130 2651_CR26 2651_CR23 2651_CR9 2651_CR6 2651_CR4 2651_CR2 2651_CR3 P Malleswararao (2651_CR21) 2011; 3 2651_CR17 2651_CR39 2651_CR38 2651_CR37 2651_CR36 2651_CR14 2651_CR13 2651_CR35 2651_CR12 2651_CR33 2651_CR32 2651_CR31 R. Simpson Angus (2651_CR1) 1994; 120 CR Suribabu (2651_CR34) 2006; 3 |
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| SubjectTerms | Algorithms Capital costs Design optimization Drinking water Environmental effects Genetic algorithms High density polyethylenes Hydraulics Linear programming Optimization Optimization techniques Pipes Python Quality of life Rural areas Sanitation Software Solution space Sustainable development Toolkits Variables Water distribution Water distribution systems Water engineering Water supply |
| Title | Optimization of water distribution network by genetic algorithm with EPANET-Python Toolkit |
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