DocumentCode :
522867
Title :
Optimal Allocation of Multi-objective Water Resources Based on Genetic Algorithm
Author :
Lianhai, Cao ; Zhiping, Li ; Nanxiang, Chen
Author_Institution :
Sch. of Resource & Environ., North China Univ. of Water Resources & Electr. Power, Zhengzhou, China
Volume :
2
fYear :
2010
fDate :
4-6 June 2010
Firstpage :
194
Lastpage :
197
Abstract :
The water resources optimization disposition of multi-water-source, the multi-consumer is the large-scale system question of multi-objective and multi-decision-making, the reasonable allocation of water resources is one of the effective regulative measures for implementing sustainable utilization of water resources. Using the inherent parallelism mechanism of genetic algorithms and global optimization characteristics, the optimal allocation of water resource problem was modeled as the problem of biological evolution, survival of the fittest was carried out by judging the degree of optimization of each generation of individuals, thus produces the new generation, iterating so repeatedly to complete the optimal allocation of water resources. The case analysis shows that this algorithm which was applied to optimize the allocation of water resources was a success.
Keywords :
decision making; genetic algorithms; large-scale systems; sustainable development; water resources; biological evolution; genetic algorithm; global optimization; large-scale system; multiconsumer; multidecision-making; multiobjective water resources; optimal water resource allocation; sustainable utilization; water resources optimization disposition; Biological cells; Biological information theory; Biological system modeling; Character generation; Evolution (biology); Genetic algorithms; Large-scale systems; Parallel processing; Resource management; Water resources; Genetic algorithm; Optimal allocation; Water resources;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information and Computing (ICIC), 2010 Third International Conference on
Conference_Location :
Wuxi, Jiang Su
Print_ISBN :
978-1-4244-7081-5
Electronic_ISBN :
978-1-4244-7082-2
Type :
conf
DOI :
10.1109/ICIC.2010.143
Filename :
5513872
Link To Document :
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