Improved genetic algorithm optimization of water distribution system design by incorporating domain knowledge

被引:119
作者
Bi, W. [1 ]
Dandy, G. C. [1 ]
Maier, H. R. [1 ]
机构
[1] Univ Adelaide, Sch Civil Environm & Min Engn, Adelaide, SA 5005, Australia
关键词
Optimization; Genetic algorithms; Water distribution systems; Domain knowledge; Heuristics; Computational efficiency; MULTIOBJECTIVE OPTIMIZATION; DISTRIBUTION NETWORKS; DECOMPOSITION;
D O I
10.1016/j.envsoft.2014.09.010
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Over the last two decades, evolutionary algorithms (EAs) have become a popular approach for solving water resources optimization problems. However, the issue of low computational efficiency limits their application to large, realistic problems. This paper uses the optimal design of water distribution systems (WDSs) as an example to illustrate how the efficiency of genetic algorithms (GAs) can be improved by using heuristic domain knowledge in the sampling of the initial population. A new heuristic procedure called the Prescreened Heuristic Sampling Method (PHSM) is proposed and tested on seven WDS cases studies of varying size. The EPANet input files for these case studies are provided as supplementary material. The performance of the PHSM is compared with that of another heuristic sampling method and two non-heuristic sampling methods. The results show that PHSM clearly performs bet overall, both in terms of computational efficiency and the ability to find near-optimal solutions. In addition, the relative advantage of using the PHSM increases with network size. (C) 2014 Elsevier Ltd. All rights reserved.
引用
收藏
页码:370 / 381
页数:12
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