Abstract: The scheduling problem is a typical time table problem in educational administration. For such a NP complete problems, when the genetic algorithm solves this problem, it has precociousness phenomenon and quickly converges not to the global optimal solution but to the local optimal solution. Therefore, we use the advantage of simulated annealing algorithm to transform the fitness function and chaotic sequence to control the crossover and mutation genetic operations and then overcome the weakness of genetic algorithm in the Time Table Problem. We do a lot of experiments and evaluate the performance of the improved genetic algorithm. The experiment results show that improved genetic algorithm is a more superior algorithm to apply to the TTP problem.