DocumentCode
518045
Title
Notice of Retraction
Chaos quantum genetic algorithm based on Tent map
Author
Teng Hao ; Zhao Bao-hua ; Wang Shi-xian
Author_Institution
Sch. of Inf. Sci. & Eng., Univ. of Ji´nan, Ji´nan, China
Volume
4
fYear
2010
fDate
16-18 April 2010
Abstract
Notice of Retraction
After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.
We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.
The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.
Aiming at the trouble of easy getting into local minimum and premature constringency existed in quantum genetic algorithm, this paper presents a new algorithm through analyzing the characteristic of Tent map and improving the quantum genetic algorithm using chaos optimization method based on Tent map. This algorithm carries through global search according to the ergodicity and randomicity of chaos movement, and can help to jump out the local minimum. The test of typical function shows that the performance of this kind of method is better than quantum genetic algorithm and genetic algorithm.
After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.
We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.
The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.
Aiming at the trouble of easy getting into local minimum and premature constringency existed in quantum genetic algorithm, this paper presents a new algorithm through analyzing the characteristic of Tent map and improving the quantum genetic algorithm using chaos optimization method based on Tent map. This algorithm carries through global search according to the ergodicity and randomicity of chaos movement, and can help to jump out the local minimum. The test of typical function shows that the performance of this kind of method is better than quantum genetic algorithm and genetic algorithm.
Keywords
chaos; genetic algorithms; quantum computing; search problems; chaos optimization method; chaos quantum genetic algorithm; global search; premature constringency; tent map; Biological cells; Chaos; Distribution functions; Genetic algorithms; Genetic engineering; Information science; Logistics; Optimization methods; Quantum computing; Testing; Tent map; chaos optimization; quantum genetic algorithm;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Engineering and Technology (ICCET), 2010 2nd International Conference on
Conference_Location
Chengdu
Print_ISBN
978-1-4244-6347-3
Type
conf
DOI
10.1109/ICCET.2010.5485510
Filename
5485510
Link To Document