Multireservoir system optimization in the Han River basin using multi-objective genetic algorithms

In this study, NSGA‐II is applied to multireservoir system optimization. Here, a four‐dimensional multireservoir system in the Han River basin was formulated. Two objective functions and three cases having different constraint conditions are used to achieve nondominated solutions. NSGA‐II effectivel...

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Vydáno v:Hydrological processes Ročník 20; číslo 9; s. 2057 - 2075
Hlavní autoři: Kim, Taesoon, Heo, Jun-Haeng, Jeong, Chang-Sam
Médium: Journal Article
Jazyk:angličtina
Vydáno: Chichester, UK John Wiley & Sons, Ltd 15.06.2006
Wiley
Témata:
Earth sciences
Earth, ocean, space
Exact sciences and technology
Freshwater
Han River basin
Hydrology
Hydrology. Hydrogeology
multi-objectives genetic algorithms
multireservoir system optimization
NSGA-II
Water resources
South Korea
Far East
Han River basin
China
Korea
China, People's Rep., Hubei Prov., Han R
algorithms
floods
NSGA-II
river discharge
reservoirs
Han River basin
multi-objectives genetic algorithms
surface water
drainage basins
multireservoir system optimization
water storage
Asia
optimization
water resource management
communities
ISSN:0885-6087, 1099-1085
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Shrnutí:In this study, NSGA‐II is applied to multireservoir system optimization. Here, a four‐dimensional multireservoir system in the Han River basin was formulated. Two objective functions and three cases having different constraint conditions are used to achieve nondominated solutions. NSGA‐II effectively determines these solutions without being subject to any user‐defined penalty function, as it is applied to a multireservoir system optimization having a number of constraints (here, 246), multi‐objectives, and infeasible initial solutions. Most research by multi‐objective genetic algorithms only reveals a trade‐off in the objective function space present, and thus the decision maker must reanalyse this trade‐off relationship in order to obtain information on the decision variable. Contrastingly, this study suggests a method for identifying the best solutions among the nondominated ones by analysing the relation between objective function values and decision variables. Our conclusions demonstrated that NSGA‐II performs well in multireservoir system optimization having multi‐objectives. Copyright © 2005 John Wiley & Sons, Ltd.
Bibliografie:ark:/67375/WNG-6KDSWJFD-2
istex:BA137534AC6F1ADD7B57333AC06079CAA939EE1D
ArticleID:HYP6047
ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
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ISSN:0885-6087
1099-1085
DOI:10.1002/hyp.6047