交通运输系统工程与信息

交通运输系统工程与信息 ›› 2020, Vol. 20 ›› Issue (2): 145-150.

• 系统工程理论与方法 • 上一篇    下一篇

公交线路配车问题的不确定双层规划模型

薛运强*1, 2, 3，郭俊1，安静1，薛逻维1，桑梓1   

  1. 1. 华东交通大学交通运输与物流学院，南昌 330013；2. 东南大学交通学院，南京 210096； 3. 江西省高铁区域发展研究中心，南昌 330013
  • 收稿日期:2019-11-04 修回日期:2019-12-05 出版日期:2020-04-25 发布日期:2020-04-30
  • 作者简介:薛运强(1983-)，男，山东新泰人，讲师，博士.
  • 基金资助:

    国家自然科学基金/ National Natural Science Foundation of China(71961006)；江西省社科规划项目青年项目/ Social Science Planning Fund Youth Project of Jiangxi Province, China(18GL37)；江西省高校人文社科基金/College Humanities and Social Sciences Fund of Jiangxi Province(GL18219).

Uncertain Bi-level Programming Model for Vehicle Allocation Problem of Bus Lines

XUE Yun-qiang1, 2, 3, GUO Jun1, AN Jing1, XUE Luo-wei1, SANG Zi1   

  1. 1. College of Transportation and Logistics, East China Jiaotong University, Nanchang 330013, China; 2. School of Transportation, Southeast University, Nanjing 210096, China; 3. High-speed Rail and Regional Development Research Center of Jiangxi Province, Nanchang 330013, China
  • Received:2019-11-04 Revised:2019-12-05 Online:2020-04-25 Published:2020-04-30

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摘要：

为合理优化公交线路配车，考虑现实中公交站点乘客数量不确定性因素，引入不确定理论构建公交线路配车的不确定双层规划模型. 上层目标为公交运营企业的收益最大化，下层目标为乘客出行时间和费用总成本最小，约束条件是政府要求的服务水平、乘车率，通过 MATLAB进行编程求解. 以南昌市210 路公交为例，利用所构建的不确定双层规划模型对早高峰07:00-08:00 配车进行优化，在给定80%乘车率的约束条件下，单方向配车数量由26 辆减少到23 辆，减少11.5%；优化后高峰小时乘客总加权成本相比优化前小幅增加0.5%，基本持平；高峰小时该线路的利润比优化前增加了112 元，提高29.6%. 结果显示，利用所构建模型优化早高峰小时线路配车效果明显. 该研究为公交运营者考虑现实中不确定因素更合理地优化线路配车提供了理论支持.

关键词: 城市交通, 线路配车, 不确定双层规划模型, 公共交通, 不确定理论

Abstract:

In order to rationally optimize the bus line allocation, this paper considers the uncertainty in passenger demand at bus stops and introduces the uncertainty theory to construct an uncertain bi-level programming model for bus line allocation. Among them, the upper- level goal is to maximize the revenue of the bus operation enterprise, and the lower-level goal is to minimize the total travel time and the cost of passengers. The constraints include the service level and the ride rate required by the government. The model is solved through Matlab programming. Taking Bus Line No. 210 in Nanchang as an example, the uncertain bi-level programming model is used to optimize the vehicle allocation in the morning peak 07:00-08:00, and under the ride rate limit of 80%. The fleet size of vehicles is reduced from 26 to 23 by 11.5%; the total weighted cost of passengers after peak hours slightly increased by 0.5%; and the profit increased by 112 yuan with a rate of 29.6% after optimization. The results show that the optimization effectiveness of the uncertain bi-level model for vehicle allocation is significant in the early peak hours. The study provides theoretical support for bus operators to rationally optimize vehicle allocation considering uncertain factors in reality.

Key words: urban traffic, vehicle allocation, uncertain bi-level programming model, public transportation, uncertainty theory

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