DocumentCode
724440
Title
The multi-objective water resources optimization scheduling based on chaos genetic algorithm
Author
Zhao Xiao-qiang ; He Zhi-e
Author_Institution
Coll. of Electr. & Inf. Eng., Lanzhou Univ. of Technol., Lanzhou, China
fYear
2015
fDate
23-25 May 2015
Firstpage
4500
Lastpage
4505
Abstract
Scheduling of water resources is the rational utilization of water resources and the main way and effective means to solve the shortage of water resources, it has some characteristics of more users, more water, multi-level and multi-objective. Chaos genetic algorithm (CGA) can be solved in the process of water resources scheduling problem such as slow convergence speed, easy to fall into local optimization, but there are some limitations in the practical application. In this paper, by using multi-objective decision scheduling, real-time and regularity of rainfall will be combined with chaos genetic algorithm (GA), a more reasonable adjustment of water supply, water resources allocation optimization. The simulation results show that multi-objective decision-making based on chaos genetic algorithm can better satisfy user needs, stick to the waste water, improve the satisfaction degree of the water, more comprehensive benefits.
Keywords
convergence; decision making; genetic algorithms; scheduling; water resources; water supply; CGA; chaos genetic algorithm; convergence speed; local optimization; multiobjective decision scheduling; multiobjective decision-making; multiobjective water resource optimization scheduling; water resource allocation optimization; water resource scheduling problem; water resource utilization; water supply; Chaos; Genetic algorithms; Job shop scheduling; Logistics; Optimization; Water resources; CGA; multi-objective decision; scheduling model; water resources optimization;
fLanguage
English
Publisher
ieee
Conference_Titel
Control and Decision Conference (CCDC), 2015 27th Chinese
Conference_Location
Qingdao
Print_ISBN
978-1-4799-7016-2
Type
conf
DOI
10.1109/CCDC.2015.7162718
Filename
7162718
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