基于元胞自动机的城市轨道交通定价双层规划

发布时间：2018-04-30 04:32

本文选题：城市轨道交通 + 票价　；参考：《管理工程学报》2017年01期

【摘要】：针对城市轨道交通建立了基于"通票"及"计程票"两种定价方式的双层规划模型;上层规划运用遗传算法对利润函数进行寻优;下层规划运用广义出行费用函数刻画乘客出行方式选择行为,并嵌入元胞遗传算法演化规则进行寻优。模拟结果显示:(1)乘客间的互动学习强度、对价格的敏感度是影响两种定价方式获利情况、对乘客分流情况的重要因素;(2)当乘客对票价的敏感度较低且学习进化行为较弱时,宜采用"通票"的定价方式;当乘客对票价的敏感度较高且学习进化行为较强时,宜采用"计程票"的定价方式。
[Abstract]:A bilevel programming model based on "pass ticket" and "meter ticket" is established for urban rail transit, and the upper planning uses genetic algorithm to optimize the profit function. The lower level programming uses the generalized travel cost function to describe the behavior of passenger travel mode selection, and embeds the evolutionary rules of cellular genetic algorithm to search for optimization. The simulation results show that the intensity of interactive learning between passengers, the sensitivity to price is an important factor affecting the profit of the two pricing methods, and the important factor of passenger diversion is when passengers are less sensitive to fares and learn less about evolutionary behavior. It is advisable to adopt the pricing method of "pass ticket", and when the passenger is more sensitive to the ticket price and to learn the evolutionary behavior, the pricing method of "meter ticket" should be adopted.
【作者单位】：北京交通大学经济管理学院;
【基金】：国家自然科学基金资助项目(71273023) 高等学校博士学科点专项科研基金资助项目(20130009110020) 中央高校基本科研业务费专项资金资助项目(2014YJS059)
【分类号】：F572.5

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