Numerous metaheuristic optimization algorithms are used for optimal design of water distribution networks. Each algorithm shows dissimilar characteristics depending on the network properties and the sensitivity analysis of the algorithm control variables. New performance metrics of metaheuristic optimization methods are proposed using simple but robust refined metrics and were applied to the available literature data for different algorithms which have previously been used for three popular benchmark water distribution networks. In general, recent performance metrics are devoted to measure effectiveness, efficiency, and reliability in a separate manner, which made some confusion, which is the best?. In the present work, the proposed metrics are used to calculate both of best global and average global performance of different optimization algorithms. The results show that the present metrics have a good distinctive performance between different algorithms. The Fittest individual referenced Differential Evolution is found to be the best algorithm.

大量的元启发式优化算法用于配水管网的优化设计。根据网络属性和算法控制变量的敏感性分析，每种算法都显示出不同的特性。使用简单但鲁棒的改进指标提出了元启发式优化方法的新性能指标，并将其应用于不同算法的可用文献数据，这些算法先前已用于三种流行的基准水分配网络。通常，最近的性能指标专门用于以单独的方式衡量有效性，效率和可靠性，这引起了一些混淆，哪是最好的？在目前的工作中，建议的指标可用于计算不同优化算法的最佳全局性能和平均全局性能。结果表明，当前指标在不同算法之间具有良好的独特性能。最适合个人的差异进化算法被认为是最好的算法。