Comparing Optimization Techniques with an Engineering Judgment Approach to WDN Design
Publication: Journal of Water Resources Planning and Management
Volume 142, Issue 5
Abstract
The design of water distribution networks (WDNs) is a complex nonlinear problem that has been solved using optimization techniques attempting to find near-globally optimal solutions. This paper demonstrates that relying on engineering judgment, with very limited use of optimization, can generate reasonable quality approximations of the Pareto front of multiobjective WDN design problems without intensive computational requirements. First the results of the implementation of a previous implementation of the engineering judgment approach to the Battle of Background Leakage Assessment for Water Networks (BBLAWN) design competition is summarized. Additionally, a simplified version of the BBLAWN problem is solved using both the engineering judgment approach and a multiobjective optimization algorithm and the corresponding Pareto fronts are compared. Relative to other BBLAWN solutions, the engineering judgment solution produced a high-quality result with a very small computational budget and was able to identify a more realistic number of changes in the WDN ( of the network) compared with BBLAWN teams relying on global optimization algorithms.
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Acknowledgments
The authors would like to thank Luigi Berardi for his assistance in providing them with the WDNetXL model of their selected solution. The authors would also like to acknowledge the combined Ontario Centres of Excellence (OCE) SmartWater and National Sciences and Engineering Research Council (NSERC) Collaborative Research and Development grant to the second author, which is supporting the graduate student first author. Thanks to the anonymous reviewers of the manuscript for improving the description of the method and the presentation of results.
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© 2015 American Society of Civil Engineers.
History
Received: Feb 1, 2015
Accepted: Aug 26, 2015
Published online: Oct 30, 2015
Discussion open until: Mar 30, 2016
Published in print: May 1, 2016
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