Abstract
The formation of district metered areas (DMAs) is an efficient strategy for the operation and management of water distribution networks (WDNs). Identifying the most suitable DMA layout is a challenging task for water utilities as it may involve several aspects that need to be addressed simultaneously. This study presents a novel multiphase approach for optimal DMA design that involves: (1) a combination of a fast Newman algorithm (FNA) to identify initial clusters; (2) a nondominated sorting genetic algorithm (NSGA-III) to obtain a set of good DMA configurations while considering several objectives simultaneously; and (3) a multiple attribute decision-making method (MADM) to find the best suited DMA configuration from a set of feasible alternative solutions based on the preference given to each objective. The proposed methodology is applied to two networks including a large benchmark network and a real-life water network. Four problem objectives out of several possible objectives were considered. These are: (1) the total cost of implementation (economic criterion); (2) the pressure deviation (hydraulic criterion); (3) a resilience index (energy criterion); and (4) the total demand shortfall (customer satisfaction criterion). Finally, a multiple attribute decision-making tool [i.e., a simple additive weighing (SAW) method] was used to arrive at a unique solution out of a set of feasible solutions. Results show that the proposed methodology can effectively identify DMAs while considering multiple objectives.
Original language | English |
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Article number | 0001586 |
Journal | Journal of Water Resources Planning and Management |
Volume | 148 |
Issue number | 8 |
DOIs | |
State | Published - Aug 1 2022 |
Bibliographical note
Publisher Copyright:© 2022 American Society of Civil Engineers.
Keywords
- District metered areas (DMAs)
- Fast Newman algorithm (FNA)
- Multiple attribute decision-making method (MADM)
- Nondominated sorting genetic algorithm (NSGA-III) algorithm
ASJC Scopus subject areas
- Civil and Structural Engineering
- Geography, Planning and Development
- Water Science and Technology
- Management, Monitoring, Policy and Law