交通运输系统工程与信息 ›› 2017, Vol. 17 ›› Issue (1): 150-156.

• 系统工程理论与方法 • 上一篇    下一篇

考虑容量限制的多公交车型运行计划优化模型

张思林,袁振洲*,曹志超   

  1. 北京交通大学城市交通复杂系统理论与技术教育部重点实验室,北京100044
  • 收稿日期:2016-09-14 修回日期:2016-11-23 出版日期:2017-02-25 发布日期:2017-02-27
  • 作者简介:张思林(1987-),女,河北秦皇岛人,博士生.
  • 基金资助:

    国家重点基础研究发展计划/ National Key Basic Research Program of China(2012CB725403).

Optimization Model of Bus Operation Plan Based on Hybrid Bus Sizes with Constraints on Vehicle Capacity

ZHANG Si-lin, YUAN Zhen-zhou, CAO Zhi-chao   

  1. MOE Key Laboratory for Urban Transportation Complex Systems Theory and Technology, Beijing Jiaotong University, Beijing 100044, China
  • Received:2016-09-14 Revised:2016-11-23 Online:2017-02-25 Published:2017-02-27

摘要:

车容量限制是公交运行计划编制的重要约束.以单条公交线为研究对象,综合考虑了不同公交车型的技术经济性能、车容量大小、车辆数限制和客流需求的时变特征等因素,建立同步优化公交车型和时刻表的规划模型,以确定线路的发车时刻表和选择车型的最优组合.建立了以公交企业运营成本和公交乘客出行成本最小为目标,带有0-1决策变量的非线性整数规划模型,针对该模型多目标函数的求解特点,采用枚举法求解每辆车的发车时刻,应用遗传算法求解车型选择的序列.最后以北京市某公交线为案例进行分析,优化后的发车时刻表和车型配置方案具有较好的运营效果.算例结果表明,采用多车型方案较传统的单一车型方案更具经济性,乘客的出行成本可减少13.9%,企业的运营成本可减少3.5%.

关键词: 城市交通, 公交运行计划, 遗传算法, 时刻表, 车型配置

Abstract:

The vehicle capacity is the important constraint of establishing bus operation plan. An optimization model is proposed for creating the bus timetables and sizing the buses, simultaneously. Based on different technical and economic properties, vehicle capacities and limited available number of heterogeneous buses, as well as the time-dependent characteristics of passenger flow demand, a binary nonlinear integer programming model is formulated to minimize the passengers’and operator’s cost. In accordance with the specialty of the model with multi-objective, enumeration method and genetic algorithm are applied to solve the frequency, departure time and dispatched order, respectively. At last, with the operation data of a bus line in Beijing, the created timetable combined with the corresponding bus type arrangement is competitive. The results suggest that the strategy of hybrid vehicle size is more economic compared to the traditional operation with only single bus type. Moreover, the passengers’cost can be reduced by 13.9% and the operator’s cost can be reduced by 3.5%.

Key words: urban traffic, bus operation plan, genetic algorithm, timetable, fleet configuration

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