Abstract: The intelligent schedule of vehicles operation is one of the problems which need to be solved in the public transportation intelligent dispatch，it relates to the economic efficiency and social benefits of transit agency.The authors use a transit vehicle scheduling model which balancing between the interests of bus companies and passengers.The particle swarm optimization algorithm with constriction factor and linear descend inertia weight，namely W-K-PSO is applied to the intelligent schedule of vehicles operation.The simulation results show that W-K-PSO has the higher efficiency than other optimization algorithm and is one effective way optimizing the public transit vehicle dispatching.

Key words: public transit vehicle dispatching, Particle Swarm Optimization（PSO）, linear descend inertia weight, constriction factor

摘要： 运营车辆的智能排班是公交车辆智能调度需要解决的问题之一，关系到公交企业的经济效益与社会效益。采用兼顾公交公司与乘客双方利益的公交车辆调度模型，将带收缩因子和线性递减惯性权重的粒子群优化算法（W-K-PSO）应用到公交智能排班中。实例仿真结果表明该算法具有比其它优化算法更好的效率，是解决公交车智能调度问题的一个有效方法。

关键词: 公交车调度, 粒子群优化, 线性递减惯性权重, 收缩因子