The fixed point theory is introduced into the genetic algorithm to optimize the convergence preci- sign of the standard genetic algorithm. The individual of the population is regarded as the triangulation of the point; hence the vertex label information of the individual simplex, which would guide the algorithm to the optimization researching and the the convergence judgment, could be calculated with the J1 triangulation and integer label. When the loading simplexes of individuals are transferred into the completely labeled simplfxes, the algorithm will be terminated and the global optimal solution will be got. The results of a computing example show that the improved genetic algorithm is stable and efficient.