Virus-evolutionary genetic algorithm-coevolution of planar grid model

Author

Kubota, Naoyuki ; Shimojima, Koji ; Fukuda, Toshio

Author_Institution

Dept. of Micro Syst. Eng., Nagoya Univ., Japan

Volume

1

fYear

1996

fDate

8-11 Sep 1996

Firstpage

232

Abstract

This paper deals with an ecological model on a planar gird of a genetic algorithm based on virus theory of evolution (E-VEGA). In the E-VEGA, each individual is placed on a planar grid and genetic operators are performed between neighborhoods. The E-VEGA can self-adaptively change searching ratio between global and local searches. The main operator of the E-VEGA is a reverse transcription operator, which plays the roles of a crossover and a selection simultaneously. The convergence and generic diversity of the E-VEGA depend on the frequency and localization of the virus infection. In this paper, we apply the E-VEGA to travelling salesman problem and discuss the coevolution of host and virus population through the numerical simulation

Keywords

convergence of numerical methods; genetic algorithms; search problems; travelling salesman problems; E-VEGA; convergence; ecological model; generic diversity; global searches; local search; optimisation; planar grid model; reverse transcription operator; travelling salesman problem; virus-evolutionary genetic algorithm; Artificial neural networks; Biological system modeling; Convergence; Evolution (biology); Frequency diversity; Fuzzy systems; Genetic algorithms; Numerical simulation; Optimization methods; Traveling salesman problems;

fLanguage

English

Publisher

ieee

Conference_Titel

Fuzzy Systems, 1996., Proceedings of the Fifth IEEE International Conference on

Conference_Location

New Orleans, LA

Print_ISBN

0-7803-3645-3

Type

conf

DOI

10.1109/FUZZY.1996.551747

Filename

551747