Real-time problem solving is an interesting topic in planning in recent years. Besides discussing the deficiency of traditional planning algorithm, the authors imported the anytime algorithm, which can solve the real-time problems in this thesis. Anytime algorithm could allocate time resource reasonably to ensure the best system output performance. Anytime algorithm could be interrupted at any time and output the relatively best probable solution in that time. Genetic algorithm has the properties of the anytime algorithm. After introducing the differences between this and other search algorithms, through the experiments, the authors found that the method, which combines the random search technology and knowledge based method, could solve real-time planning problems relatively better that other methods. At last, the authors gave out the conclusion, discussed the policy of real-time planning problem solving algorithm simply, and discussed the possible developments in the future.