Immune algorithm for n-TSP

Author

Endoh, Satoshi ; Toma, Naruaki ; Yamada, Koji

Author_Institution

Fac. of Eng., Ryukyus Univ., Okinawa, Japan

Volume

4

fYear

1998

fDate

11-14 Oct 1998

Firstpage

3844

Abstract

As the neural networks or genetic algorithms, adaptive algorithms become popular and these techniques are applied to many kinds of optimization problems. The immune system is one of the adaptive biological system whose functions are to identify and to eliminate foreign material. In this paper, we propose an optimization algorithm based on immune model and applied to the n-th agents´ travelling salesman problem called n-TSP. Some computer simulations are designed to investigate the performance of the immune algorithm. The results of simulations represent that the immune algorithm shows good performance for the combinatorial optimization problems

Keywords

adaptive systems; travelling salesman problems; adaptive biological system; combinatorial optimization problems; computer simulations; foreign material elimination; foreign material identification; immune algorithm; multiagent travelling salesman problem; n-TSP; optimization problems; Adaptive algorithm; Adaptive systems; Biological materials; Biological system modeling; Biological systems; Computer simulation; Genetic algorithms; Immune system; Neural networks; Traveling salesman problems;

fLanguage

English

Publisher

ieee

Conference_Titel

Systems, Man, and Cybernetics, 1998. 1998 IEEE International Conference on

Conference_Location

San Diego, CA

ISSN

1062-922X

Print_ISBN

0-7803-4778-1

Type

conf

DOI

10.1109/ICSMC.1998.726687

Filename

726687