Improved genetic algorithm optimization of water distribution system design by incorporating domain knowledge. (July 2015)

• Record Type: Journal Article
• Authors: Bi, W.; Dandy, G.C.; Maier, H.R.
• Is Part Of: Environmental modelling & software. Volume 69(2015:Jul.)
• Page Start: 370
• Page End: 381
• Publication Date: 2015-07
• Subjects: Optimization -- Genetic algorithms -- Water distribution systems -- Domain knowledge -- Heuristics -- Computational efficiency; Environmental monitoring -- Computer programs -- Periodicals; Ecology -- Computer simulation -- Periodicals; Digital computer simulation -- Periodicals; Computer software -- Periodicals; Environmental Monitoring -- Periodicals; Computer Simulation -- Periodicals; Environnement -- Surveillance -- Logiciels -- Périodiques; Écologie -- Simulation, Méthodes de -- Périodiques; Simulation par ordinateur -- Périodiques; Logiciels -- Périodiques; Computer software; Digital computer simulation; Ecology -- Computer simulation; Environmental monitoring -- Computer programs; Periodicals; Electronic journals; 363.70015118
• DOI: 10.1016/j.envsoft.2014.09.010
• Languages: English
• ISSNs: 1364-8152

Abstract

Abstract: 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 best 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. Highlights: A new heuristic sampling method is introduced for the optimization of WDSs using GAs. The proposed PHSM performs better than three other sampling methods. The advantages are both in efficiency and the ability to find near-optimal solutions. The relative advantage of using the PHSM increases with network size and complexity.