DocumentCode :
1992948
Title :
Immunity Genetic Algorithm Based on Elitist Strategy and Its Application to the TSP Problem
Author :
Yan, Liang ; Kongyu, Yang
Author_Institution :
Sch. of Econ. & Manage., Beijing Inf. Sci. & Technol. Univ., Beijing
Volume :
2
fYear :
2008
fDate :
21-22 Dec. 2008
Firstpage :
729
Lastpage :
732
Abstract :
In order to improve searching efficiency and prevent premature in the standard GA, a new immune genetic algorithm is proposed and designed based on elitist strategy of its complete convergence and immune memory mechanism in the immune system. Through comparing the solutions of TSP problem with between the standard GA and IMGA, then complete convergence and good computation complicacy of the IMGA is analyzed to prove much better than the standard GA.The excellent availability on searching efficiency has some practical significance.
Keywords :
artificial immune systems; genetic algorithms; search problems; travelling salesman problems; TSP problem; elitist strategy; immune memory mechanism; immune system; immunity genetic algorithm; local search method; Character generation; Convergence; Educational technology; Evolution (biology); Genetic algorithms; Genetic engineering; Genetic mutations; Immune system; Knowledge management; Management training;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Education Technology and Training, 2008. and 2008 International Workshop on Geoscience and Remote Sensing. ETT and GRS 2008. International Workshop on
Conference_Location :
Shanghai
Print_ISBN :
978-0-7695-3563-0
Type :
conf
DOI :
10.1109/ETTandGRS.2008.407
Filename :
5070466
Link To Document :
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