Non-parametric optimization technique for water distribution in pipe networks
Water distribution networks (WDN) contribute the massive cost of pipes in total water distribution system (WDS) design, thus the optimal design of any WDN is more of a necessity than a requirement. Various evolutionary algorithms (EAs) proposed in the past involve the use of algorithm-specific param...
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creator | Palod, Nikita Prasad, Vishnu Khare, Ruchi |
description | Water distribution networks (WDN) contribute the massive cost of pipes in total water distribution system (WDS) design, thus the optimal design of any WDN is more of a necessity than a requirement. Various evolutionary algorithms (EAs) proposed in the past involve the use of algorithm-specific parameters and their synchronizing to get the optimal solution and thus require more computational effort and time. To overcome this drawback, the present work introduces an optimization technique, JayaNet, which is the integration of the Jaya algorithm and hydraulic network solver EPANET 2. The best part of this technique is that no algorithm-specific parameter is to be synchronized for optimal cost but there needs to be adjustment of penalty parameter and population size based on network size. Four well-known benchmark networks with different sizes and layout have been taken and optimized using JayaNet. The results are compared with those obtained from other EAs. It is found that optimized costs obtained for four networks by JayaNet are either the same or less than the results obtained from other EAs even with a lower number of function evaluations (NFE). The NFE are found to increase with population size in all networks. The statistical parameter obtained from JayaNet is also compared for different networks. |
doi_str_mv | 10.2166/ws.2020.200 |
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Various evolutionary algorithms (EAs) proposed in the past involve the use of algorithm-specific parameters and their synchronizing to get the optimal solution and thus require more computational effort and time. To overcome this drawback, the present work introduces an optimization technique, JayaNet, which is the integration of the Jaya algorithm and hydraulic network solver EPANET 2. The best part of this technique is that no algorithm-specific parameter is to be synchronized for optimal cost but there needs to be adjustment of penalty parameter and population size based on network size. Four well-known benchmark networks with different sizes and layout have been taken and optimized using JayaNet. The results are compared with those obtained from other EAs. It is found that optimized costs obtained for four networks by JayaNet are either the same or less than the results obtained from other EAs even with a lower number of function evaluations (NFE). The NFE are found to increase with population size in all networks. The statistical parameter obtained from JayaNet is also compared for different networks.</description><identifier>ISSN: 1606-9749</identifier><identifier>EISSN: 1607-0798</identifier><identifier>DOI: 10.2166/ws.2020.200</identifier><language>eng</language><publisher>London: IWA Publishing</publisher><subject>Algorithms ; Computer applications ; Design ; Design optimization ; Distribution ; Evolutionary algorithms ; Genetic algorithms ; Linear programming ; Mutation ; Networks ; Nonparametric statistics ; Optimization ; Optimization techniques ; Parameters ; Population ; Population (statistical) ; Population number ; Simulation ; Synchronism ; Water distribution ; Water distribution systems ; Water engineering ; Water shortages</subject><ispartof>Water science & technology. 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Water supply</title><description>Water distribution networks (WDN) contribute the massive cost of pipes in total water distribution system (WDS) design, thus the optimal design of any WDN is more of a necessity than a requirement. Various evolutionary algorithms (EAs) proposed in the past involve the use of algorithm-specific parameters and their synchronizing to get the optimal solution and thus require more computational effort and time. To overcome this drawback, the present work introduces an optimization technique, JayaNet, which is the integration of the Jaya algorithm and hydraulic network solver EPANET 2. The best part of this technique is that no algorithm-specific parameter is to be synchronized for optimal cost but there needs to be adjustment of penalty parameter and population size based on network size. Four well-known benchmark networks with different sizes and layout have been taken and optimized using JayaNet. The results are compared with those obtained from other EAs. It is found that optimized costs obtained for four networks by JayaNet are either the same or less than the results obtained from other EAs even with a lower number of function evaluations (NFE). The NFE are found to increase with population size in all networks. The statistical parameter obtained from JayaNet is also compared for different networks.</description><subject>Algorithms</subject><subject>Computer applications</subject><subject>Design</subject><subject>Design optimization</subject><subject>Distribution</subject><subject>Evolutionary algorithms</subject><subject>Genetic algorithms</subject><subject>Linear programming</subject><subject>Mutation</subject><subject>Networks</subject><subject>Nonparametric statistics</subject><subject>Optimization</subject><subject>Optimization techniques</subject><subject>Parameters</subject><subject>Population</subject><subject>Population (statistical)</subject><subject>Population number</subject><subject>Simulation</subject><subject>Synchronism</subject><subject>Water distribution</subject><subject>Water distribution systems</subject><subject>Water engineering</subject><subject>Water shortages</subject><issn>1606-9749</issn><issn>1607-0798</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><sourceid>AFKRA</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><recordid>eNotkEtLAzEUhYMoWKsr_0DApUy9eTSPpRStQtVN90Mmk8FUOxmTDIP-emPr5t574OOew0HomsCCEiHuprSgQIsAOEEzIkBWILU6Pdyi0pLrc3SR0g6ASknoDL28hr4aTDR7l6O3OAzZ7_2PyT70ODv73vuv0eEuRDyZ7CJufSpgMx4A3-PBDw73Lk8hfqRLdNaZz-Su_vccbR8ftqunavO2fl7dbypLtcqVhI5YLaSWTHHKacMax61pnZGwJMaITjNliNNL3jaGdg4ol1ZoLRVjTcvm6Ob4doihpEu53oUx9sWxplwRyiRXvFC3R8rGkFJ0XT1EvzfxuyZQ_9VVT4UvdZUB7Bf60l42</recordid><startdate>20201201</startdate><enddate>20201201</enddate><creator>Palod, Nikita</creator><creator>Prasad, Vishnu</creator><creator>Khare, Ruchi</creator><general>IWA Publishing</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7QH</scope><scope>7UA</scope><scope>8FE</scope><scope>8FG</scope><scope>ABJCF</scope><scope>AFKRA</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>BHPHI</scope><scope>BKSAR</scope><scope>C1K</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>F1W</scope><scope>H96</scope><scope>H97</scope><scope>HCIFZ</scope><scope>L.G</scope><scope>L6V</scope><scope>M7S</scope><scope>PCBAR</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PTHSS</scope></search><sort><creationdate>20201201</creationdate><title>Non-parametric optimization technique for water distribution in pipe networks</title><author>Palod, Nikita ; 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Water supply</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Palod, Nikita</au><au>Prasad, Vishnu</au><au>Khare, Ruchi</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Non-parametric optimization technique for water distribution in pipe networks</atitle><jtitle>Water science & technology. Water supply</jtitle><date>2020-12-01</date><risdate>2020</risdate><volume>20</volume><issue>8</issue><spage>3068</spage><epage>3082</epage><pages>3068-3082</pages><issn>1606-9749</issn><eissn>1607-0798</eissn><abstract>Water distribution networks (WDN) contribute the massive cost of pipes in total water distribution system (WDS) design, thus the optimal design of any WDN is more of a necessity than a requirement. Various evolutionary algorithms (EAs) proposed in the past involve the use of algorithm-specific parameters and their synchronizing to get the optimal solution and thus require more computational effort and time. To overcome this drawback, the present work introduces an optimization technique, JayaNet, which is the integration of the Jaya algorithm and hydraulic network solver EPANET 2. The best part of this technique is that no algorithm-specific parameter is to be synchronized for optimal cost but there needs to be adjustment of penalty parameter and population size based on network size. Four well-known benchmark networks with different sizes and layout have been taken and optimized using JayaNet. The results are compared with those obtained from other EAs. It is found that optimized costs obtained for four networks by JayaNet are either the same or less than the results obtained from other EAs even with a lower number of function evaluations (NFE). The NFE are found to increase with population size in all networks. The statistical parameter obtained from JayaNet is also compared for different networks.</abstract><cop>London</cop><pub>IWA Publishing</pub><doi>10.2166/ws.2020.200</doi><tpages>15</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Algorithms Computer applications Design Design optimization Distribution Evolutionary algorithms Genetic algorithms Linear programming Mutation Networks Nonparametric statistics Optimization Optimization techniques Parameters Population Population (statistical) Population number Simulation Synchronism Water distribution Water distribution systems Water engineering Water shortages |
title | Non-parametric optimization technique for water distribution in pipe networks |
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