A Dynamic Genetic Algorithm Based on Numeric Encoding

In this paper we propose a dynamic genetic algorithm based on numeric encoding. We find that the numeric encoding can overcome the limitation of precision and the introduction of characteristic crossover and mutation mechanism can guide the crossover operations consciously and decrease the loss of genes caused by aimlessness of mutation. The algorithm improves the speed of convergence of the solution and makes the global optimal procedure more efficient. Furthermore, it successfully avoids the occurrence of premature converge and the validity and efficiency of the proposed.