DocumentCode
3310276
Title
An Improved Mutative Scale Chaos Optimization Quantum Genetic Algorithm
Author
Teng, Hao ; Zhao, Baohua ; Yang, Bingru
Author_Institution
Sch. of Inf. Eng., Univ. of Sci. & Technol. Beijing, Beijing
Volume
6
fYear
2008
fDate
18-20 Oct. 2008
Firstpage
301
Lastpage
305
Abstract
The theory of chaos optimization is introduced in this paper; and through improving the constringency strategy of mutative scale chaos optimization method, we can enhance the efficiency and the performance of chaos optimization method; then aiming at the trouble of easy getting into local minimum existed in quantum genetic algorithm, this paper presents a new chaos quantum genetic algorithm. Using the improved mutative scale chaos optimization method, chaotic search for the optimization is implemented to the population which is processed one time with the quantum genetic algorithm, which can lead to the rapid evolution of the population. The test of typical function shows that the performance of this method is better than quantum genetic algorithm and genetic algorithm.
Keywords
chaos; genetic algorithms; quantum computing; chaos quantum genetic algorithm; mutative scale chaos optimization; Chaos; Convergence; Decision making; Genetic algorithms; Genetic engineering; Information science; Optimization methods; Quantum computing; Quantum mechanics; Testing; Chaos Optimization; Constringency Strategy; Mutative Scale; Quantum Genetic Algorithm;
fLanguage
English
Publisher
ieee
Conference_Titel
Natural Computation, 2008. ICNC '08. Fourth International Conference on
Conference_Location
Jinan
Print_ISBN
978-0-7695-3304-9
Type
conf
DOI
10.1109/ICNC.2008.739
Filename
4667849
Link To Document