Preliminary analysis of multi-objective genetic algorithm application for multireservoir system

Taesoon Kim; Jun Haeng Heo

Preliminary analysis of multi-objective genetic algorithm application for multireservoir system

Department of Civil and Environmental Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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.

Original language	English
Title of host publication	31st IAHR Congress 2005
Subtitle of host publication	Water Engineering for the Future, Choices and Challenges
Editors	Jun Byong-Ho, Il Lee Sang, Seo Il Won, Choi Gye-Woon
Publisher	Korea Water Resources Association
Pages	5535-5543
Number of pages	9
ISBN (Electronic)	8987898245, 9788987898247
Publication status	Published - 2005 Jan 1
Event	31st IAHR Congress 2005: Water Engineering for the Future, Choices and Challenges - Seoul, Korea, Republic of Duration: 2005 Sep 11 → 2005 Sep 16

Publication series

Name	31st IAHR Congress 2005: Water Engineering for the Future, Choices and Challenges

Conference

Conference	31st IAHR Congress 2005: Water Engineering for the Future, Choices and Challenges
Country	Korea, Republic of
City	Seoul
Period	05/9/11 → 05/9/16

All Science Journal Classification (ASJC) codes

Engineering (miscellaneous)
Environmental Science (miscellaneous)
Water Science and Technology

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Kim, T., & Heo, J. H. (2005). Preliminary analysis of multi-objective genetic algorithm application for multireservoir system. In J. Byong-Ho, I. L. Sang, S. I. Won, & C. Gye-Woon (Eds.), 31st IAHR Congress 2005: Water Engineering for the Future, Choices and Challenges (pp. 5535-5543). (31st IAHR Congress 2005: Water Engineering for the Future, Choices and Challenges). Korea Water Resources Association.

Kim, Taesoon ; Heo, Jun Haeng. / Preliminary analysis of multi-objective genetic algorithm application for multireservoir system. 31st IAHR Congress 2005: Water Engineering for the Future, Choices and Challenges. editor / Jun Byong-Ho ; Il Lee Sang ; Seo Il Won ; Choi Gye-Woon. Korea Water Resources Association, 2005. pp. 5535-5543 (31st IAHR Congress 2005: Water Engineering for the Future, Choices and Challenges).

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title = "Preliminary analysis of multi-objective genetic algorithm application for multireservoir system",

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.",

author = "Taesoon Kim and Heo, {Jun Haeng}",

year = "2005",

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series = "31st IAHR Congress 2005: Water Engineering for the Future, Choices and Challenges",

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Kim, T & Heo, JH 2005, Preliminary analysis of multi-objective genetic algorithm application for multireservoir system. in J Byong-Ho, IL Sang, SI Won & C Gye-Woon (eds), 31st IAHR Congress 2005: Water Engineering for the Future, Choices and Challenges. 31st IAHR Congress 2005: Water Engineering for the Future, Choices and Challenges, Korea Water Resources Association, pp. 5535-5543, 31st IAHR Congress 2005: Water Engineering for the Future, Choices and Challenges, Seoul, Korea, Republic of, 05/9/11.

Preliminary analysis of multi-objective genetic algorithm application for multireservoir system. / Kim, Taesoon; Heo, Jun Haeng.

31st IAHR Congress 2005: Water Engineering for the Future, Choices and Challenges. ed. / Jun Byong-Ho; Il Lee Sang; Seo Il Won; Choi Gye-Woon. Korea Water Resources Association, 2005. p. 5535-5543 (31st IAHR Congress 2005: Water Engineering for the Future, Choices and Challenges).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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N2 - 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.

AB - 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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Kim T, Heo JH. Preliminary analysis of multi-objective genetic algorithm application for multireservoir system. In Byong-Ho J, Sang IL, Won SI, Gye-Woon C, editors, 31st IAHR Congress 2005: Water Engineering for the Future, Choices and Challenges. Korea Water Resources Association. 2005. p. 5535-5543. (31st IAHR Congress 2005: Water Engineering for the Future, Choices and Challenges).