Abstract: In this paper,the cloud genetic algorithm(CGA) was introduced by the combination of cloud model theory and genetic algorithms(GA).The Y-conditional cloud generator for the normal cloud model is used as cross operation in this hybrid genetic algorithm,and the basic cloud generator is used as the mutation operator in the optimization operation of GA.Both the cross and the mutation operation make use of the randomness and stability of cloud to improve the algorithm convergence,robustness and the solutions quality.And also it overcomes the traditional GA shortcomings such as slow searching,easy to local optimization solutions.The simulation test shows that the proposed hybrid algorithm can improve the vehicular scheduling efficiency and feasibility for the public transport.The scheduling solutions from this algorithm were also validated through the service quality evaluation and show well application prospect.