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合理的票价分级策略往往能够使得公交乘客和经营者实现“双赢”的局面.为了制定合理的票价分级策略，本文首先通过SP调查采集乘客的选择意向信息，研究了影响乘客广义费用函数的因素变化规律，采用统计分析的方法建立了广义费用函数；其次，以乘客广义费用最小和公交经营者经营效益最大为目标，建立票价分级策略的双层优化模型；最后，基于遗传算法设计了该模型的求解方法，并以济南市2路公交做实例研究.结果表明，本文所研究的基于遗传算法的公交票价分级策略不仅能够使公交乘客的综合效用增加，而且能够使经营者的收益有所提高.

Bus Fare Classification with Genetic Algorithm

A reasonable fare classification strategy can often make the bus passengers and operators achieve a "win-win" situation.To realize that,the information of passenger choice is collected by a SP survey,the key factors affecting the generalized cost are identifited and the function of the generalized cost is formulated by the statistical analysis method.Then a method of fare classification based on the bi-level programming model is developed by taking the maximum generalized cost and maximum interests of operation as the ultimate goal.The model is solved by the genetic algorithm,and the bus line 2 in Jinan city of China is taken as an example to verify the rationality of the model.The result shows the model can raise not only the generalized cost of the bus passenger but the interest of the operators.