Genetic Algorithm Based on Virus Theory of Evolution for Traveling Salesman Problem
暂无分享,去创建一个
This paper deals with virus evolutionary genetic algorithm. The genetic algorithms (GAs)) have been demonstrated its effectiveness in optimization problems in these days. In general, the GAs simulate the survival of fittest by natural selection and the heredity of the Darwin's theory of evolution. However, some types of evolutionary hypotheses such as neutral theory of molecular evolution, Imanishi's evolutionary theory, serial symbiosis theory, and virus theory of evolution, have been proposed in addition to the Darwinism. Virus theory of evolution is based on the view that the virus transduction is a key mechanism for transporting segments of DNA across species. This paper proposes genetic algorithm based on the virus theory of evolution (VE-GA), which has two types of populations: host population and virus population. The VE-GA is composed of genetic operators and virus operators such as reverse transcription and incorporation. The reverse transcription operator transcribes virus genes on the chromosome of host individual and the incorporation operator creates new genotype of virus from host individual. These operators by virus population make it possible to transmit segment of DNA between individuals in the host population. Therefore, the VE-GA realizes not only vertical but also horizontal propagation of genetic information. Further, the VE-GA is applied to the traveling salesman problem in order to show the effectiveness.
[1] Gilbert Syswerda,et al. A Study of Reproduction in Generational and Steady State Genetic Algorithms , 1990, FOGA.
[2] T. Fukuda,et al. Genetic algorithm with age structure and its application to self-organizing manufacturing system , 1994, ETFA '94. 1994 IEEE Symposium on Emerging Technologies and Factory Automation. (SEIKEN) Symposium) -Novel Disciplines for the Next Century- Proceedings.
[3] 敏男 福田,et al. 動的再構成可能ロボットシステムに関する研究 : 第11報, Genetic Algorithmを用いた協調型形態構成手順の生成 , 1992 .