DocumentCode
514996
Title
Notice of Retraction
Immune Genetic Algorithm and Its Application on Job Shop Scheduling
Author
Qiao Wei ; Li Qiaoyun ; Ju Chuanbao ; Sun Jie
Author_Institution
Lab. & Equip. Manage. Office, Shandong Univ. at Weihai, Weihai, China
Volume
2
fYear
2010
fDate
6-7 March 2010
Firstpage
11
Lastpage
14
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.
To overcome the shortcoming of ordinary genetic algorithm, an immune genetic algorithm is designed to better solve the job shop scheduling. Based on the characteristic that optimal offspring of each generation corresponding to the workpiece machining order is favorable to the target function, the algorithm abstracts vaccine and employs the improved elitist-crossover strategy and the simulated-annealing-based vaccine selection method. The simulation tests have showed the validity and practicability of the algorithm, and that the algorithm has better convergence speed and optimization accuracy. Specially, as a result of the algorithm, the prematurity which is a common phenomenon in the ordinary genetic algorithm, is efficiently avoided.
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.
To overcome the shortcoming of ordinary genetic algorithm, an immune genetic algorithm is designed to better solve the job shop scheduling. Based on the characteristic that optimal offspring of each generation corresponding to the workpiece machining order is favorable to the target function, the algorithm abstracts vaccine and employs the improved elitist-crossover strategy and the simulated-annealing-based vaccine selection method. The simulation tests have showed the validity and practicability of the algorithm, and that the algorithm has better convergence speed and optimization accuracy. Specially, as a result of the algorithm, the prematurity which is a common phenomenon in the ordinary genetic algorithm, is efficiently avoided.
Keywords
genetic algorithms; job shop scheduling; simulated annealing; convergence speed; immune genetic algorithm; job shop scheduling; optimal offspring; simulated annealing based vaccine selection method; target function; workpiece machining; Abstracts; Algorithm design and analysis; Character generation; Convergence; Genetic algorithms; Job design; Job shop scheduling; Machining; Testing; Vaccines; Elitist-crossover; Immune Genetic Algorithm; Job Shop scheduling; Vaccine;
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.2010.518
Filename
5460077
Link To Document