考虑到地铁与公交站间距的差异，将两种方式协同服务下的乘客按照其可选择路径的不同分为三种类型。在此基础上对两种方式的票价和换乘优惠进行优化，并详尽分析不同类型乘客之间的相互影响和对最优票价及换乘优惠的影响。为解决这样一个问题，本文构建一个双层规划模型：上层追求社会福利的最大化，下层为基于弹性需求的随机用户均衡模型；并采用遗传算法对双层规划模型进行求解。最后，通过算例对所建模型进行验证；结果表明：①在对地铁与公交的票价及换乘优惠的优化中，不可忽略两种方式站间距的差异；②考虑站间距差异后，两种方式的最优票价有所提高，且其票价及换乘优惠之间的差值均将减少。%Considering the stop spacing difference between subway and bus services, passengers served by both services are classified into three types according to their chosen trip paths. The fares and transfer pricing discounts of the two services are optimized in an integrated model that captures the interaction of different passenger type trip and the influence of it on optimal fares and transfer pricing discounts. For this purpose, a bi-level program is formulated, of which the upper level aims to maximize the social welfare and the lower level is a variable-demand stochastic user equilibrium assignment model. The genetic algorithm is applied to solve the bi-level program. Numerical experiments are carried out to illustrate the performance of the model. The results show that: ① it is of great significance to embed the factor of stop spacing difference between subway and bus services into the integrated optimization of fares and transfer pricing discounts of the two services, otherwise overcrowding may emerge in a set of routes in each service line; ② the optimal fares of each service can increase and both the differences between fares of the two services and transfer pricing discounts are reduced considering the stop spacing difference.
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