Novel survival of the fittest genetic algorithm

In order to prevent premature convergence of evolution population, a novel closed crossing avoidance strategy is presented by considering the relationship between diversity of evolution population andevolutiontimes.Thelowerlimit of closed crossing avoidance varies with evolution times and average Hamming distance of evolution population. A novel survival of the fittest genetic algorithm is presented. The algorithm can avoid close breeding effectively and externalize the thought of survival of the fittest. It has been proved that the algorithm can converge to globally optimal solution. Simulation result shows that the algorithm presented is efficient contrast with simple genetic algorithm.