An efficient decomposition and dual-stage multi-objective optimization method for water distribution systems with multiple supply sources
An efficient decomposition and dual-stage multi-objective optimization method for water distribution systems with multiple supply sources
复制标题
DOI：
10.1016/j.envsoft.2014.01.028
复制
发表时间：
2014-05
期刊：
影响因子：
--
通讯作者：
Feifei Zheng;A. Zecchin
中科院分区：
文献类型：
--
作者：
Feifei Zheng;A. Zecchin
提出了一种有效的多水源供水管网优化设计的分解和两阶段多目标优化方法。提出的DDMO方法涉及三个阶段。在阶段1中，为WDS-MSS识别最优源划分割集，从而允许将整个WDS-MSS分解成子网络。然后在第二阶段采用非支配排序遗传算法（NSGA-II）分别优化子网络，从而为每个子网络产生最优前沿。最后，在第3阶段，另一个NSGA-II实现用于驱动组合子网络前沿（近似最优前沿）朝向原始完整WDS-MSS的帕累托前沿。四个WDS-MSS被用来证明所提出的方法的有效性。结果表明，建议的DDMO显着优于NSGA-II，优化整个网络作为一个整体，有效地找到高质量的最优前沿。
This paper proposes an efficient decomposition and dual-stage multi-objective optimization (DDMO) method for designing water distribution systems with multiple supply sources (WDS-MSSs). Three phases are involved in the proposed DDMO approach. In Phase 1, an optimal source partitioning cut-set is identified for a WDS-MSS, allowing the entire WDS-MSS to be decomposed into sub-networks. Then in Phase 2 a non-dominated sorting genetic algorithm (NSGA-II) is employed to optimize the sub-networks separately, thereby producing an optimal front for each sub-network. Finally in Phase 3, another NSGA-II implementation is used to drive the combined sub-network front (an approximate optimal front) towards the Pareto front for the original complete WDS-MSS. Four WDS-MSSs are used to demonstrate the effectiveness of the proposed approach. Results obtained show that the proposed DDMO significantly outperforms the NSGA-II that optimizes the entire network as a whole in terms of efficiently finding good quality optimal fronts.