TY - JOUR
T1 - Multi-period consequence management of contaminations in water distribution networks
T2 - application of regret-based optimization model
AU - Masoumi, Fariborz
AU - Zafari, Negin
AU - Nematollahi, Banafsheh
AU - Nikoo, Mohammad Reza
N1 - Publisher Copyright:
© 2022 Informa UK Limited, trading as Taylor & Francis Group.
PY - 2022
Y1 - 2022
N2 - This study presents a Regret-based optimization model for multi-period consequence management of contaminations entering the WDNs considering the pollutants loads’ entry uncertainties. For this purpose, first, the EPANET software is utilized as a water quality-quantity simulation modeling tool. Then, an optimization model based on a genetic algorithm using the primary objective functions of minimizing the return time of the contaminated WDNs to the normal mode, the amount of pollution, and the number of polluted nodes. Besides, the pollutant load-related uncertainties are included in the presented simulation-optimization model by minimizing the maximum Regret (MMR) and the total Regret (MTR) in two steady and dynamic status for all three mentioned objective functions. Using these nine objective functions, three management instruments are utilized: quick closing valves, discharging hydrants, and boosting pumps. The results show that the proposed model can effectively prevent harmful pollution by offering effective management strategies, mainly in dynamic status scenarios.
AB - This study presents a Regret-based optimization model for multi-period consequence management of contaminations entering the WDNs considering the pollutants loads’ entry uncertainties. For this purpose, first, the EPANET software is utilized as a water quality-quantity simulation modeling tool. Then, an optimization model based on a genetic algorithm using the primary objective functions of minimizing the return time of the contaminated WDNs to the normal mode, the amount of pollution, and the number of polluted nodes. Besides, the pollutant load-related uncertainties are included in the presented simulation-optimization model by minimizing the maximum Regret (MMR) and the total Regret (MTR) in two steady and dynamic status for all three mentioned objective functions. Using these nine objective functions, three management instruments are utilized: quick closing valves, discharging hydrants, and boosting pumps. The results show that the proposed model can effectively prevent harmful pollution by offering effective management strategies, mainly in dynamic status scenarios.
KW - Consequence management strategies
KW - contamination
KW - EPANET software
KW - genetic algorithm (GA)
KW - regret theory
KW - water distribution network (WDN)
UR - http://www.scopus.com/inward/record.url?scp=85144044134&partnerID=8YFLogxK
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U2 - 10.1080/1573062X.2022.2154681
DO - 10.1080/1573062X.2022.2154681
M3 - Article
AN - SCOPUS:85144044134
SN - 1573-062X
JO - Urban Water Journal
JF - Urban Water Journal
ER -