An improved genetic algorithm and its performance analysis

In the paper, some general theorems-minimal resolution, weight value, and searching step of crossover and mutation of the chromosome searching step in a genetic algorithm based on binary coding, one-point, crossover, and bit mutation are proposed and proved. Based on these theorems, an improved genetic algorithm using variant chromosome length and probability of crossover and mutation is presented. Finally, testing with some critical functions shows that it can improve the convergence speed of the genetic algorithm significantly and it accords with theoretic deduction, and its comprehensive performance is better than that of the genetic algorithm which only reserves the best individual.