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