DocumentCode
518706
Title
Notice of Retraction
Cloning particle swarm optimization with hybrid discrete variables and its application to gear reducer
Author
Youxin Luo ; Bin Zeng
Author_Institution
Coll. of Mech. Eng., Hunan Univ. of Arts & Sci., Changde, China
Volume
3
fYear
2010
fDate
27-29 March 2010
Firstpage
395
Lastpage
398
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.
During the iterative process of standard particle swarm optimization (PSO), the premature convergence of particles decreases the algorithm´s searching ability. Through analyzing the reason of particle premature convergence during the renewal process, introducing the updating strategy based on cloning technique, cloning particle swarm optimization (CPSO) algorithm with hybrid discrete variables model was proposed, and its program CPSO1.0 with Matlab software was developed. The updating strategy based on cloning algorithm makes the particles of cloning particle swarm optimization (CPSO) maintain the diversity during the iterative process, thus overcomes the defect of premature convergence. Example of gear reducer indicates that compared with the exiting algorithms, CPSO gets the best result, thus certify the improvement of the algorithm´s searching ability by cloning mechanism.
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.
During the iterative process of standard particle swarm optimization (PSO), the premature convergence of particles decreases the algorithm´s searching ability. Through analyzing the reason of particle premature convergence during the renewal process, introducing the updating strategy based on cloning technique, cloning particle swarm optimization (CPSO) algorithm with hybrid discrete variables model was proposed, and its program CPSO1.0 with Matlab software was developed. The updating strategy based on cloning algorithm makes the particles of cloning particle swarm optimization (CPSO) maintain the diversity during the iterative process, thus overcomes the defect of premature convergence. Example of gear reducer indicates that compared with the exiting algorithms, CPSO gets the best result, thus certify the improvement of the algorithm´s searching ability by cloning mechanism.
Keywords
gears; iterative methods; particle swarm optimisation; CPSO1.0; cloning mechanism; cloning particle swarm optimization; gear reducer; hybrid discrete variables; iterative process; particle premature convergence; Algorithm design and analysis; Art; Cloning; Convergence; Educational institutions; Evolutionary computation; Gears; Iterative algorithms; Mechanical engineering; Particle swarm optimization; Cloning Algorithm; Cloning particle swarm optimization; gear reducer; hybrid discrete variables;
fLanguage
English
Publisher
ieee
Conference_Titel
Advanced Computer Control (ICACC), 2010 2nd International Conference on
Conference_Location
Shenyang
Print_ISBN
978-1-4244-5845-5
Type
conf
DOI
10.1109/ICACC.2010.5486830
Filename
5486830
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