Heuristic-Based Approach for Near-Optimal Response to Water Distribution Network Failures in Near Real Time
Publication: Journal of Water Resources Planning and Management
Volume 148, Issue 8
Abstract
This paper proposes a new method to identify the near-optimal response to failures in water distribution networks in near real time. The response method is formulated as a two-objective optimization problem with objectives being the minimization of failure impacts and related operational costs. The new heuristics-based method is developed and used to solve this optimization problem. The method comprises three steps. In the first step, the initial list of available interventions is identified offline. In the second step (online), the narrowed-down list of interventions considered in the optimization is identified. Finally, in the last step (online), a novel heuristic algorithm is applied to identify near-optimal solutions in near real time. The new optimization method was validated and demonstrated in two case studies, a semireal case study based on a C-Town network and an assumed failure event (pipe burst), and a real UK case study involving a complex real pipe network and event caused by shutting down the Water Treatment Works. The Pareto front of response interventions identified by the new heuristics method approximates well the non-dominated sorting genetic algorithm II Pareto front in both cases with the largest differences measured in terms of end-impacts (between relevant solutions for the same cost) being 4% and 9%, respectively. In addition, the new heuristics method is able to identify near-optimal response solutions in a computationally fast manner (15 min and 1 h for the two cases). Therefore, the heuristics method can be used in near real time in real-life situations.
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Data Availability Statement
All data, models, and code that support the findings of this study are available from the corresponding author upon reasonable request.
Acknowledgments
This work was funded as part of the Water Informatics Science and Engineering Centre for Doctoral Training (WISE CDT) under a grant from the Engineering and Physical Sciences Research Council (EPSRC) (Grant No. EP/L016214/1), as well as from United Utilities. The present work has made use of resources, data, and information provided by United Utilities.
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Published In
Journal of Water Resources Planning and Management
Volume 148 • Issue 8 • August 2022
Copyright
© 2022 American Society of Civil Engineers.
History
Received: Jan 12, 2021
Accepted: Mar 26, 2022
Published online: May 27, 2022
Published in print: Aug 1, 2022
Discussion open until: Oct 27, 2022
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