A Virus Co-evolution Genetic Algorithm Based on Niche Technology

In order to avoid premature convergence and improve global search efficiency of the standard genetic algorithm (SGA) a novel virus co-evolution genetic algorithm based on niche technology (NVEGA) is developed. The virus co-evolution algorithm raises the efficiency of global convergence and accelerates local search by vertical search between child and parent generations and horizontal search among the same generation respectively, where virus populations vertically inherit excellent patterns from the outstanding family of their host populations, subsequently they horizontally pass them on to the child host populations so as to preserve and propagate good patterns from the parent host populations. As a result in the course of evolution of the host populations virus populations evolve themselves by importing the excellent patterns from their host populations and in turn accelerate evolution of host populations. Furthermore the niche technology is adopted to avoid premature convergence, enrich the variety of the population, and enhance capacity of global search. Finally a function optimization sample is given to illustrate the performance of this hybrid genetic algorithm.