DocumentCode :
1946817
Title :
Genetic Algorithms for Optimization of Complex Nonlinear System
Author :
Song Chaohong ; Luo Qiang ; Shi Feng
Author_Institution :
Dept. of Inf. & Comput. Sci., Huazhong Agric. Univ., Wuhan
Volume :
1
fYear :
2008
fDate :
12-14 Dec. 2008
Firstpage :
378
Lastpage :
381
Abstract :
Reasonable dimension reduction and effective optimization calculation are the basic ways to study the optimization of complex nonlinear system. A method based on the traditional decomposition technology is put forward to solve the optimization problem of complex nonlinear system, of which decision variable is decomposed to independence variable and coupling variable. On the basis of this method, genetic algorithms to solve the coupling variable and the traditional optimization technology to solve the independence variable are also established. This method has been used to a drainage optimal planning of a closed polder system. The result indicates that the method can obtain the optimum relation rapidly. It also can improve the calculation efficiency as well as avoid the difficultly to obtain the global optimal solution of the traditional optimization technology. This method can be applied to solve the similar optimization problem of other complex nonlinear systems.
Keywords :
decision theory; genetic algorithms; large-scale systems; linear programming; nonlinear programming; nonlinear systems; closed polder system; complex nonlinear system; coupling variable; decision variable decomposition; drainage optimal planning; genetic algorithm; global optimal solution; independence variable; linear programming; nonlinear programming; optimization; reasonable dimension reduction; Chaos; Computer science; Constraint optimization; Genetic algorithms; Genetic mutations; Laboratories; Linear programming; Nonlinear systems; Optimization methods; Software engineering; genetic algorithm; nonlinear system; optimization problem;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Science and Software Engineering, 2008 International Conference on
Conference_Location :
Wuhan, Hubei
Print_ISBN :
978-0-7695-3336-0
Type :
conf
DOI :
10.1109/CSSE.2008.758
Filename :
4721766
Link To Document :
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