多方式弹性需求下公交定价双层规划模型

发布时间：2018-09-03 16:45

【摘要】：为描述多方式城市交通网络下公交定价与出行选择行为的相互作用与影响,将出行方式选择与路径选择涵盖于同一网络,建立了上层模型分别以企业利润最大化、乘客出行成本最小化和社会福利最大化为目标函数,下层模型为多方式弹性需求随机用户配流模型的公交定价双层规划模型。运用改进遗传算法对模型整体进行求解,下层模型采用综合对角化算法和MSA算法的组合求解算法。最后,设计了一个算例以说明模型应用。结果表明:运用双层规划模型所确定的公交票价较传统静态票价可使政府、企业及出行者三方都获得更高收益,且上层模型以社会福利最大化为目标函数能代表社会群体中多数人利益,优化效果最为理想。
[Abstract]:In order to describe the interaction and influence of bus pricing and travel choice behavior in multi-mode urban transportation network, the travel mode choice and route choice are covered in the same network, and the upper layer model is established to maximize the profit of the enterprise respectively. Passenger travel cost minimization and social welfare maximization are objective functions. The lower level model is a multi-mode elastic demand stochastic user allocation model of public transport pricing bilevel programming model. The improved genetic algorithm is used to solve the whole model, and the lower model is solved by the combination of integrated diagonalization algorithm and MSA algorithm. Finally, an example is designed to illustrate the application of the model. The results show that the public transport fares determined by the bilevel programming model can make the government, enterprises and travelers get higher returns than the traditional static fares. The upper model takes the social welfare maximization as the objective function to represent the interests of the majority of the social groups, and the optimization effect is the most ideal.
【作者单位】：重庆交通大学山地城市交通系统与安全重庆市重点实验室;重庆交通大学交通运输学院;
【基金】：国家自然科学基金项目(51308569) 重庆市教委科学技术研究项目(KJ130424) 科技部863计划项目子课题(2011AA11306) (重庆交通大学)开放基金项目(CQSLBF-Y13-1)
【分类号】：F572

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