2022
DOI: 10.1061/(asce)wr.1943-5452.0001586
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Multiphase Procedure for Identifying District Metered Areas in Water Distribution Networks Using Community Detection, NSGA-III Optimization, and Multiple Attribute Decision Making

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Cited by 17 publications
(3 citation statements)
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“…This method is particularly suitable for solving double -objective optimization problems , but when solving optimization problems with more than three objectives , the individuals selected by the crowding distance ranking are not uniformly distributed on the non -dominated level and easily fall int o local optimality, affecting the convergence and diversity of the algorithm (Li et al, 2019). The NSGA-III algorithm introduces the concept of uniformly distributed reference points by extending the NSGA -II selection method and uses a predefined multiobjective search method that can effectively overcome the problems of non-dominated solutions , invalid crossover, and variation and provides good convergence and diversity solutions in high -dimensional cases (Sharma et al, 2022a ). The number of objective functions in this model is six, which is a high -dimensional multi -objective optimization , so the NSGA-III algorithm is used as a tool for encoding and optimization.…”
Section: Solving Algorithmmentioning
confidence: 99%
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“…This method is particularly suitable for solving double -objective optimization problems , but when solving optimization problems with more than three objectives , the individuals selected by the crowding distance ranking are not uniformly distributed on the non -dominated level and easily fall int o local optimality, affecting the convergence and diversity of the algorithm (Li et al, 2019). The NSGA-III algorithm introduces the concept of uniformly distributed reference points by extending the NSGA -II selection method and uses a predefined multiobjective search method that can effectively overcome the problems of non-dominated solutions , invalid crossover, and variation and provides good convergence and diversity solutions in high -dimensional cases (Sharma et al, 2022a ). The number of objective functions in this model is six, which is a high -dimensional multi -objective optimization , so the NSGA-III algorithm is used as a tool for encoding and optimization.…”
Section: Solving Algorithmmentioning
confidence: 99%
“…Leakage is the main cause of water loss in WDNs and raises potential environmental and health risks in addition to huge economic losses (Puust et al, 2010 ). However, dividing WDNs into district metered areas (DMAs) has proven effective in reducing leakage (Morrison et al, 2007 ;Sharma et al, 2022a ). DMAs are achieved by installing valves (or disconnecting pipe s) on some pipes and adding flow meters to form several discrete areas and by monitoring the amount of water entering and leaving each area and analyzing the flow to quantify leakage levels, based on which water utilities can accurately determine where leakage occurs and carry out timely repai r work (Morrison et al, 2007 ).…”
Section: Introductionmentioning
confidence: 99%
“…A widely adopted metric in the context of WDN partitioning ( [9][10][11]) is modularity [12], which effectively quantifies the goodness of network subdivision into communities (in terms of balanced cluster sizes and few boundary links). In this regard, the recently developed modularity-based procedure by Creaco et al 2023 [13], originally conceived for a dual WDN topology (segment/valve graphs), can be used for the clustering of the standard node/pipe topology.…”
Section: Introductionmentioning
confidence: 99%