DocumentCode
2284829
Title
Notice of Retraction
Artificial Fish-Swarm Algorithm with Chaos and Its Application
Author
Zhaohui Chen ; Xuequan Tian
Author_Institution
Dept. of Math. & Phys., Chongqing Univ. of Sci. & Technol., Chongqing, China
Volume
1
fYear
2010
fDate
6-7 March 2010
Firstpage
226
Lastpage
229
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.
According to the characteristics of Artificial Fish-swarm Algorithm and Chaos Optimization Algorithm, A kind of artificial Fish-Swarm Algorithm with Chaos is constructed by adding chaos to influence the update of the velocities of artificial fish, so that precocious phenomenon is suppressed, the convergence rate and the accuracy is improved. By testing two functions and NP hard problems of the Planar Location Problem, the experimental results show that the algorithm is an efficient global optimization algorithm for solving global optimization problem.
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.
According to the characteristics of Artificial Fish-swarm Algorithm and Chaos Optimization Algorithm, A kind of artificial Fish-Swarm Algorithm with Chaos is constructed by adding chaos to influence the update of the velocities of artificial fish, so that precocious phenomenon is suppressed, the convergence rate and the accuracy is improved. By testing two functions and NP hard problems of the Planar Location Problem, the experimental results show that the algorithm is an efficient global optimization algorithm for solving global optimization problem.
Keywords
computational complexity; optimisation; NP hard problems; artificial fish-swarm algorithm; chaos audits application; chaos optimization algorithm; global optimization algorithm; planar location problem; Chaos; Computer science education; Convergence; Educational technology; Genetic mutations; Marine animals; Mathematics; Physics; Stochastic processes; Testing; AFSA; artificial fish-swarm algorithm with chaos; chaos; global optimization; planar location problem;
fLanguage
English
Publisher
ieee
Conference_Titel
Education Technology and Computer Science (ETCS), 2010 Second International Workshop on
Conference_Location
Wuhan
Print_ISBN
978-1-4244-6388-6
Type
conf
DOI
10.1109/ETCS.2010.253
Filename
5458996
Link To Document