Even the most carefully designed water distribution network (WDN) can suffer from local capacity deficiencies as a result of the quick and unpredictable growth of the urbanization of new industrial sites. To solve this problem, this paper focuses on the identification of the best possible location for a new pipeline within an existing WDN, which maximizes the node-wise capacity. To determine the optimal solution, a parameter, namely pressure sensitivity, is defined, which can localize nodes with local capacity problems computationally efficiently. During our research, a fitness function transformation technique was defined, which increases the effectivity of the optimization on a larger scale by the formulation of a feasible fitness function. Combining this technique with an extended version of the genetic algorithm, the topology of eleven real-life WDN was optimized. A scrutiny is performed on three networks, highlighting typical deficiencies.

由于新工业区城市化的快速和不可预测的增长，即使是最精心设计的供水网络 (WDN) 也会受到当地容量不足的影响。为了解决这个问题，本文重点介绍了在现有 WDN 内为新管道确定最佳可能位置，从而最大限度地提高节点容量。为了确定最优解，定义了一个参数，即压力敏感性，它可以有效地计算具有局部容量问题的节点。在我们的研究中，定义了一种适应度函数转换技术，它通过制定可行的适应度函数来提高更大规模优化的有效性。将此技术与遗传算法的扩展版本相结合，优化了 11 个真实 WDN 的拓扑结构。对三个网络进行了审查，突出了典型的缺陷。