交通运输系统工程与信息 ›› 2017, Vol. 17 ›› Issue (6): 207-213.

• 城市轨道交通网络化运营理论与方法 • 上一篇    下一篇

城市轨道交通网络单程票卡调配模型

姚向明,赵鹏,王琦   

  1. 北京交通大学交通运输学院,北京100044
  • 收稿日期:2017-06-08 修回日期:2017-08-29 出版日期:2017-12-25 发布日期:2017-12-25
  • 作者简介:姚向明(1987-),男,湖北宜昌人,讲师.
  • 基金资助:

    国家自然科学基金/National Natural Science Foundation of China(51478036,71701011);中央高校基本科研业务费专项资金/ The Fundamental Research Funds for the Central Universities(2017RC032).

Dispatching Model for Single-journey Ticket Cards in Urban Rail Transit Network

YAO Xiang-ming, ZHAO Peng,WANG Qi   

  1. School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, China
  • Received:2017-06-08 Revised:2017-08-29 Online:2017-12-25 Published:2017-12-25

摘要:

城市轨道交通单程票卡调配是票务组织中的重要组成部分.针对路网票务中心与线路票务中心间票卡调配问题,将其转化为载重能力约束条件下的车辆路径优化问题(Vehicle Routing Problem, VRP),构建以配送成本最小化为目标,以配送车辆路径为决策变量的优化模型,并采用遗传算法求解.以北京市轨道交通网络为对象进行实证分析,结果显示:所构建方法相比单次配送过程,成本平均降低约49.6%;相比既有装卸混合条件下的配送过程,成本降低约18.7%,验证了模型的准确性与有效性.所构建方法能够有效解决轨道交通路网层票卡调配问题,为票务组织提供理论和方法支持.

关键词: 城市交通, 票卡调配, 车辆路径优化, 遗传算法, 装卸混合

Abstract:

The dispatching of single-journey ticket cards is an important part of ticket organization in urban rail transit system. To address the ticket cards dispatching issue between network ticket center and line ticket center, a vehicle routing method under capacity constraint is used, which aims to minimize the delivery cost. The paths of each vehicle is applied as decision variables in the model, and a genetic algorithm is used to solve the model. The Beijing rail transit is taken to carry on the case study. Results show that: compared to the independent single-way delivery process, the cost reduced by about 49.6%; compared to the traditional vehicle routing method under the condition of delivery and pickup simultaneously, the cost reduced by about 18.7%, which verifies the accuracy and validity of the proposed model. The method can effectively solve the ticket dispatching problem in rail transit network and provide theoretical and method support for ticketing organizations.

Key words: urban traffic, ticket cards dispatching, vehicle routing optimization, genetic algorithm, delivery and pickup simultaneously

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