在优化配水系统方面已经做了大量的研究。该领域的早期研究使用了传统的优化技术，如线性和非线性规划。最近，遗传算法（GAs）已成功地应用于现实世界的网络规划和设计问题。自1994年以来，文献中已经报道了遗传算法优化的一些实际应用。作为系统扩展研究的一部分，这些论文的重点是使用遗传算法优化技术来确定优化的资本改善方案。报告的结果非常有希望，与传统设计程序相比，预计资本成本节省高达50%。本文描述了GA优化的另一个重要应用，不同于识别优化的资本改善计划，该计划涉及调查操作设定点和操作程序，以实现配电系统问题的最佳整体解决方案。 系统运行的改进可能基于以下目标:降低运营和能源成本、提高服务水平、降低风险、提供维护计划或优化现有资产的利用率。本文给出了三个案例研究，以说明如何制定遗传算法来优化不同的运营决策，从而最小化项目的生命周期成本。

Considerable research has been done on the optimiztion of water distribution systems. Early research in this area used traditional optimization techniques such as linear and non-linear programming. More recently, genetic algorithms (GAs) have been applied successfully to real-world network planning and design problems. Since 1994, a number of practical applications of GA optimization have been reported in the literature. The focus of these papers has been on the use of the GA optimization technique to identify optimized capital improvement alternatives as part of a system expansion study. The reported results have been very promising with projected capital cost savings of up to 50% when compared to traditional design procedures. This paper describes another important application of GA optimization distinct from the identification of optimized capital improvement plans that involves the investigation of opertional set points and operating procedures to achieve the best overall solution for a distribution system problem. Improvements to system operations may be based on objectives such as reducing operating and energy costs, improving the level of service, lowering risks, providing for maintenance scheduling, or optimizing the utilization of existing assets. Three case studies are presented to illustrate how the GA can be formulated to optimize different operational decisions with the objective of minimizing the lifetime cost of the project.