2024
DOI: 10.3390/w16020359
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Study on the Optimization of Wujiang’s Water Resources by Combining the Quota Method and NSGA-II Algorithm

Yongyu Qu,
Bo Song,
Shubing Cai
et al.

Abstract: Recently, the Chinese government has implemented stringent water requirements based on the concept of ‘Basing four aspects on water resources’. However, existing research has inadequately addressed the constraints of water resources on population, city boundaries, land, and production, failing to adequately analyze the interplay between water resource limitations and urban development. Recognizing the interconnectedness between urban water use and economic development, a multi-objective model becomes crucial f… Show more

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Cited by 3 publications
(2 citation statements)
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“…Furthermore, to achieve the rational placement of strain sensors in a structural-health-monitoring system, Del Priore et al [38] innovated a sensor placement strategy for structural-health-monitoring systems with NSGA-II. Finally, to maximize urban GDP and minimize total water resources, Qu et al [39] has applied the NSGA-II algorithm to solve a non-linear multi-objective model, addressing the inherent information loss problems of the traditional water quota method. Recognized for aiding decision-makers in navigating conflicting goals, the INSGA-II algorithm emerges as a solution tailored to the NP-hard nature of these optimization problems.…”
Section: Algorithm Selectionmentioning
confidence: 99%
“…Furthermore, to achieve the rational placement of strain sensors in a structural-health-monitoring system, Del Priore et al [38] innovated a sensor placement strategy for structural-health-monitoring systems with NSGA-II. Finally, to maximize urban GDP and minimize total water resources, Qu et al [39] has applied the NSGA-II algorithm to solve a non-linear multi-objective model, addressing the inherent information loss problems of the traditional water quota method. Recognized for aiding decision-makers in navigating conflicting goals, the INSGA-II algorithm emerges as a solution tailored to the NP-hard nature of these optimization problems.…”
Section: Algorithm Selectionmentioning
confidence: 99%
“…NSGA-II algorithm [26], as a multiobjective optimization algorithm, can directly optimize and solve multi-objective problems with good optimization effect and fast optimization speed [27]. NSGA-II algorithm has been widely used in aerospace [28], machine design [29], reservoir optimization scheduling [30], resource scheduling [31], power systems [32], and many other fields. For example, in reservoir scheduling, Chang [33] et al applied the NSGA-II algorithm to the reservoir group optimal scheduling problem and tested the feasibility and effectiveness of the algorithm in the multi-objective optimal scheduling of reservoirs.…”
Section: Introductionmentioning
confidence: 99%