Multireservoir system optimization using multi-objective genetic algorithms

Taesoon Kim; Jun Haeng Heo

Multireservoir system optimization using multi-objective genetic algorithms

Taesoon Kim, Jun Haeng Heo

Department of Civil and Environmental Engineering

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

9 Citations (Scopus)

Abstract

The application of multi-objective genetic algorithms (MOGA) to optimize system of the Han River basin in South Korea was discussed. The solutions of the MOGA yielded a trade-off curve or surface, identifying a population of points that define optimal solutions to the problem. It was found that non-dominating sorting approach was used to get the non-dominated fronts and maintaining a diverse set of solutions in the non-dominated fronts was achieved by sharing. The results show that MOGA has been an effective solution technique for solving multireservoir system optimization.

Original language	English
Title of host publication	Proceedings of the 2004 World Water and Environmetal Resources Congress
Subtitle of host publication	Critical Transitions in Water and Environmental Resources Management
Editors	G. Sehlke, D.F. Hayes, D.K. Stevens
Pages	1900-1909
Number of pages	10
Publication status	Published - 2004
Event	2004 World Water and Environmental Resources Congress: Critical Transitions in Water and Environmental Resources Management - Salt Lake City, UT, United States Duration: 2004 Jun 27 → 2004 Jul 1

Publication series

Name	Proceedings of the 2004 World Water and Environmetal Resources Congress: Critical Transitions in Water and Environmetal Resources Management

Other

Other	2004 World Water and Environmental Resources Congress: Critical Transitions in Water and Environmental Resources Management
Country/Territory	United States
City	Salt Lake City, UT
Period	04/6/27 → 04/7/1

All Science Journal Classification (ASJC) codes

Engineering(all)

Cite this

Kim, T., & Heo, J. H. (2004). Multireservoir system optimization using multi-objective genetic algorithms. In G. Sehlke, D. F. Hayes, & D. K. Stevens (Eds.), Proceedings of the 2004 World Water and Environmetal Resources Congress: Critical Transitions in Water and Environmental Resources Management (pp. 1900-1909). (Proceedings of the 2004 World Water and Environmetal Resources Congress: Critical Transitions in Water and Environmetal Resources Management).

Kim, Taesoon ; Heo, Jun Haeng. / Multireservoir system optimization using multi-objective genetic algorithms. Proceedings of the 2004 World Water and Environmetal Resources Congress: Critical Transitions in Water and Environmental Resources Management. editor / G. Sehlke ; D.F. Hayes ; D.K. Stevens. 2004. pp. 1900-1909 (Proceedings of the 2004 World Water and Environmetal Resources Congress: Critical Transitions in Water and Environmetal Resources Management).

@inproceedings{ef10bc66287e48679efb8e6c712bb390,

title = "Multireservoir system optimization using multi-objective genetic algorithms",

abstract = "The application of multi-objective genetic algorithms (MOGA) to optimize system of the Han River basin in South Korea was discussed. The solutions of the MOGA yielded a trade-off curve or surface, identifying a population of points that define optimal solutions to the problem. It was found that non-dominating sorting approach was used to get the non-dominated fronts and maintaining a diverse set of solutions in the non-dominated fronts was achieved by sharing. The results show that MOGA has been an effective solution technique for solving multireservoir system optimization.",

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

year = "2004",

language = "English",

isbn = "0784407371",

series = "Proceedings of the 2004 World Water and Environmetal Resources Congress: Critical Transitions in Water and Environmetal Resources Management",

pages = "1900--1909",

editor = "G. Sehlke and D.F. Hayes and D.K. Stevens",

booktitle = "Proceedings of the 2004 World Water and Environmetal Resources Congress",

note = "2004 World Water and Environmental Resources Congress: Critical Transitions in Water and Environmental Resources Management ; Conference date: 27-06-2004 Through 01-07-2004",

}

Kim, T & Heo, JH 2004, Multireservoir system optimization using multi-objective genetic algorithms. in G Sehlke, DF Hayes & DK Stevens (eds), Proceedings of the 2004 World Water and Environmetal Resources Congress: Critical Transitions in Water and Environmental Resources Management. Proceedings of the 2004 World Water and Environmetal Resources Congress: Critical Transitions in Water and Environmetal Resources Management, pp. 1900-1909, 2004 World Water and Environmental Resources Congress: Critical Transitions in Water and Environmental Resources Management, Salt Lake City, UT, United States, 04/6/27.

Multireservoir system optimization using multi-objective genetic algorithms. / Kim, Taesoon; Heo, Jun Haeng.

Proceedings of the 2004 World Water and Environmetal Resources Congress: Critical Transitions in Water and Environmental Resources Management. ed. / G. Sehlke; D.F. Hayes; D.K. Stevens. 2004. p. 1900-1909 (Proceedings of the 2004 World Water and Environmetal Resources Congress: Critical Transitions in Water and Environmetal Resources Management).

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

TY - GEN

T1 - Multireservoir system optimization using multi-objective genetic algorithms

AU - Kim, Taesoon

AU - Heo, Jun Haeng

PY - 2004

Y1 - 2004

N2 - The application of multi-objective genetic algorithms (MOGA) to optimize system of the Han River basin in South Korea was discussed. The solutions of the MOGA yielded a trade-off curve or surface, identifying a population of points that define optimal solutions to the problem. It was found that non-dominating sorting approach was used to get the non-dominated fronts and maintaining a diverse set of solutions in the non-dominated fronts was achieved by sharing. The results show that MOGA has been an effective solution technique for solving multireservoir system optimization.

AB - The application of multi-objective genetic algorithms (MOGA) to optimize system of the Han River basin in South Korea was discussed. The solutions of the MOGA yielded a trade-off curve or surface, identifying a population of points that define optimal solutions to the problem. It was found that non-dominating sorting approach was used to get the non-dominated fronts and maintaining a diverse set of solutions in the non-dominated fronts was achieved by sharing. The results show that MOGA has been an effective solution technique for solving multireservoir system optimization.

UR - http://www.scopus.com/inward/record.url?scp=23844513514&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=23844513514&partnerID=8YFLogxK

M3 - Conference contribution

AN - SCOPUS:23844513514

SN - 0784407371

T3 - Proceedings of the 2004 World Water and Environmetal Resources Congress: Critical Transitions in Water and Environmetal Resources Management

SP - 1900

EP - 1909

BT - Proceedings of the 2004 World Water and Environmetal Resources Congress

A2 - Sehlke, G.

A2 - Hayes, D.F.

A2 - Stevens, D.K.

T2 - 2004 World Water and Environmental Resources Congress: Critical Transitions in Water and Environmental Resources Management

Y2 - 27 June 2004 through 1 July 2004

ER -

Kim T, Heo JH. Multireservoir system optimization using multi-objective genetic algorithms. In Sehlke G, Hayes DF, Stevens DK, editors, Proceedings of the 2004 World Water and Environmetal Resources Congress: Critical Transitions in Water and Environmental Resources Management. 2004. p. 1900-1909. (Proceedings of the 2004 World Water and Environmetal Resources Congress: Critical Transitions in Water and Environmetal Resources Management).

Multireservoir system optimization using multi-objective genetic algorithms

Abstract

Publication series

Other

All Science Journal Classification (ASJC) codes

Other files and links

Fingerprint

Cite this