A novel survival of the fittest genetic algorithm
Fengping Pan, Xiaoyan Sun, Xu Shifan, Xijin Guo, Dunwei Gong · 2003
Considering the relationship between the variety of evolution population and evolution times, a novel closed crossing avoidance strategy is put forth in this paper. Based on it, a novel survival of the fittest genetic algorithm is present. The algorithm can avoid close breeding effectively and the thought of survival of the fittest is externalized. It has been proved that the algorithm can converge to an optimal solution globally. Simulation shows that the algorithm present in this paper is an efficient contrast with the simple genetic algorithm.