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Preliminary Analysis of Multi-Objective Genetic Algorithm Application for Multireservoir System

Author(s): Taesoon Kim; Jun-Haeng Heo

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Keywords: Multireservoir system optimization; Multi-objectives genetic algorithms; NSGA-II; Han River basin

Abstract: In this study, NSGA-II is applied to multireservoir system optimization, and the appropriate distribution index is suggested. Here, a four dimensional multireservoir system in the Han River basin was formulated. Two objective functions 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, conflicting two multi- objectives. Most research by MOGAs only reveals a trade-off in the objective function space present, and thus the decision-maker must re-analyze 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 analyzing the relation between objective function values and decision variables. Our conclusions demonstrate that NSGA-II performs well in multireservoir system optimization having multi-objectives.

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Year: 2005

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