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The differential evolution(DE) algorithm has been received increasing attention in terms of optimizing the design for the water distribution systems(WDSs).This paper aims to carry out a comprehensive performance comparison between the new emerged DE algorithm and the most popular algorithm-the genetic algorithm(GA).A total of six benchmark WDS case studies were used with the number of decision variables ranging from 8 to 454.A preliminary sensitivity analysis was performed to select the most effective parameter values for both algorithms to enable the fair comparison.It is observed from the results that the DE algorithm consistently outperforms the GA in terms of both efficiency and the solution quality for each case study.Additionally,the DE algorithm was also compared with the previously published optimization algorithms based on the results for those six case studies,indicating that the DE exhibits comparable performance with other algorithms.It can be concluded that the DE is a newly promising optimization algorithm in the design of WDSs.
The differential evolution (DE) algorithm has been given increased attention in terms of optimizing the design for the water distribution systems (WDSs) .This paper aims to carry out a comprehensive performance comparison between the new emer DE algorithm and the most popular algorithm-the genetic algorithm (GA). A total of six benchmark WDS case studies were used with the number of decision variables ranging from 8 to 454. A preliminary sensitivity analysis was performed to select the most effective parameter values for both algorithms to enable the fair comparison. It is observed from the results that the DE algorithm consistently outperforms the GA in terms of both efficiency and the solution quality for each case study. Additionally, the DE algorithm was also compared with the previously published optimization algorithms based on the results for those six cases studies, indicating that the DE exhibiting comparable performance with other algorithms. It can be concluded that the DE is a new ly promising optimization algorithm in the design of WDSs.