Virus-evolutionary genetic algorithm-coevolution of planar grid model

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