TY - GEN
T1 - Multireservoir system optimization using multi-objective genetic algorithms
AU - Kim, Taesoon
AU - Heo, Jun Haeng
N1 - Copyright:
Copyright 2008 Elsevier B.V., All rights reserved.
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.
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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 -