TY - JOUR
T1 - Multi-objective optimization of hydrant flushing in a water distribution system using a fast hybrid technique
AU - Shoorangiz, Mostafa
AU - Nikoo, Mohammad Reza
AU - Šimůnek, Jirka
AU - Gandomi, Amir H.
AU - Adamowski, Jan Franklin
AU - Al-Wardy, Malik
N1 - Publisher Copyright:
© 2023 Elsevier Ltd
PY - 2023/5/15
Y1 - 2023/5/15
N2 - As a critical element in preserving the health of urban populations, water distribution systems (WDSs) must be ready to implement emergency plans when catastrophic events such as contamination events occur. A risk-based simulation-optimization framework (EPANET–NSGA-III) combined with a decision support model (GMCR) is proposed in this study to determine optimal locations for contaminant flushing hydrants under an array of potentially hazardous scenarios. Risk-based analysis using Conditional Value-at-Risk (CVaR)-based objectives can address uncertainties regarding the mode of WDS contamination, thereby providing a robust plan to minimize the associated risks at a 95% confidence level. Conflict modeling by GMCR achieved an optimal compromise solution within the Pareto front by identifying a final stable consensus among the decision-makers involved. A novel hybrid contamination event grouping-parallel water quality simulation technique was incorporated into the integrated model to reduce model runtime, the main deterrent in optimization-based methods. The nearly 80% reduction in model runtime made the proposed model a viable solution for online simulation-optimization problems. The framework's capacity to address real-world problems was evaluated for the WDS operating in Lamerd, a city in Fars Province, Iran. Results showed that the proposed framework was capable of highlighting a single flushing strategy, which not only optimally reduced risks associated with contamination events, but provided acceptable coverage against such threats, flushing 35–61.3% of input contamination mass on average, and reducing average time-to-return to normal conditions by 14.4–60.2%, while employing less than half of the initial potential hydrants.
AB - As a critical element in preserving the health of urban populations, water distribution systems (WDSs) must be ready to implement emergency plans when catastrophic events such as contamination events occur. A risk-based simulation-optimization framework (EPANET–NSGA-III) combined with a decision support model (GMCR) is proposed in this study to determine optimal locations for contaminant flushing hydrants under an array of potentially hazardous scenarios. Risk-based analysis using Conditional Value-at-Risk (CVaR)-based objectives can address uncertainties regarding the mode of WDS contamination, thereby providing a robust plan to minimize the associated risks at a 95% confidence level. Conflict modeling by GMCR achieved an optimal compromise solution within the Pareto front by identifying a final stable consensus among the decision-makers involved. A novel hybrid contamination event grouping-parallel water quality simulation technique was incorporated into the integrated model to reduce model runtime, the main deterrent in optimization-based methods. The nearly 80% reduction in model runtime made the proposed model a viable solution for online simulation-optimization problems. The framework's capacity to address real-world problems was evaluated for the WDS operating in Lamerd, a city in Fars Province, Iran. Results showed that the proposed framework was capable of highlighting a single flushing strategy, which not only optimally reduced risks associated with contamination events, but provided acceptable coverage against such threats, flushing 35–61.3% of input contamination mass on average, and reducing average time-to-return to normal conditions by 14.4–60.2%, while employing less than half of the initial potential hydrants.
KW - Contamination event grouping
KW - Hydrant flushing
KW - Parallel water quality simulation
KW - Risk-based analysis
KW - Runtime reduction
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U2 - 10.1016/j.jenvman.2023.117463
DO - 10.1016/j.jenvman.2023.117463
M3 - Article
C2 - 36801802
AN - SCOPUS:85148328567
SN - 0301-4797
VL - 334
JO - Journal of Environmental Management
JF - Journal of Environmental Management
M1 - 117463
ER -