Optimal reservoir flood operation using a decomposition-based multi-objective evolutionary algorithm

Reservoir flood control operation (RFCO) is a challenging optimization problem with interdependent decision variables and multiple conflicting criteria. By considering safety both upstream and downstream of the dam, a multi-objective optimization model is built for RFCO. To solve this problem, a mul...

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Bibliographic Details
Published in:Engineering optimization Vol. 51; no. 1; pp. 42 - 62
Main Authors: Zhang, Xiao, Luo, Jungang, Sun, Xiaomei, Xie, Jiancang
Format: Journal Article
Language:English
Published: Abingdon Taylor & Francis 02.01.2019
Taylor & Francis Ltd
Subjects:
Dam safety
Decomposition
differential evolution
Evolutionary algorithms
Flood control
Floods
Genetic algorithms
multi-objective evolutionary algorithm
Multiple objective analysis
Optimization
Reservoir flood control operation
ISSN:0305-215X, 1029-0273
Online Access:Get full text
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Summary:Reservoir flood control operation (RFCO) is a challenging optimization problem with interdependent decision variables and multiple conflicting criteria. By considering safety both upstream and downstream of the dam, a multi-objective optimization model is built for RFCO. To solve this problem, a multi-objective optimizer, the multi-objective evolutionary algorithm based on decomposition-differential evolution (MOEA/D-DE), is developed by introducing a differential evolution-inspired recombination into the algorithmic framework of the decomposition-based multi-objective optimization algorithm, which has been proven to be effective for solving complex multi-objective optimization problems. Experimental results on four typical floods at the Ankang reservoir illustrated that the suggested algorithm outperforms or performs as well as the comparison algorithms. It can significantly reduce the flood peak and also guarantee the dam's safety.
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ISSN:0305-215X
1029-0273
DOI:10.1080/0305215X.2018.1439942