Immunity Genetic Algorithm Based on Elitist Strategy and its Application to the TSP Problem

Author

Yan, Liang ; Kongyu, Yang

Author_Institution

Beijing Res. Center for Knowledge Manage., Beijing Inf. Sci.& Technol. Univ., Beijing

fYear

2008

fDate

21-22 Dec. 2008

Firstpage

3

Lastpage

6

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

genetic algorithms; travelling salesman problems; TSP problem; elitist strategy; immune memory mechanism; immunity genetic algorithm; searching efficiency; Character generation; Convergence; Evolution (biology); Genetic algorithms; Genetic engineering; Genetic mutations; Immune system; Information technology; Knowledge management; Technology management; TSP; elitist strategye; genetic algorithm; immmune memory;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Information Technology Application Workshops, 2008. IITAW '08. International Symposium on

Conference_Location

Shanghai

Print_ISBN

978-0-7695-3505-0

Type

conf

DOI

10.1109/IITA.Workshops.2008.20

Filename

4731867