Genetic Algorithm with Selective Generation

摘要

Deeply analyze the charactistic of genetic operator(selection opertor, crossover operator, mutation operator) of general Genetic Algorithm. The random of the algorithm causes not all of computing steps of Genetic Algorithm towards the maximal individual and then increases the computing time. The paper introduces conceptions of selective generation and provides a method, in which every step selects some special individuals for reproduction to avoid random and blindness at some degree, eventually, to improve speed of computing. Comparing by general Genetic Algorithm, simulation results of optimizing some functions show that the method has more fast convergence speed.