计算机科学 ›› 2017, Vol. 44 ›› Issue (10): 269-275.doi: 10.11896/j.issn.1002-137X.2017.10.049

• 人工智能 • 上一篇    下一篇

基于发车时刻表的单线公交组合调度模型

王洋,沈记全   

  1. 河南理工大学计算机科学与技术学院 焦作454003,河南理工大学计算机科学与技术学院 焦作454003
  • 出版日期:2018-12-01 发布日期:2018-12-01
  • 基金资助:
    本文受河南省基础与前沿研究项目(152300410212)资助

Single Line Transit Mixed Scheduling Model Based on Vehicle Departure Timetable

WANG Yang and SHEN Ji-quan   

  • Online:2018-12-01 Published:2018-12-01

摘要: 针对目前全程车和大站快车的单线公交组合调度模型中对乘客的分类及滞站乘客乘车处理方法的不足,分3个步骤对模型进行了补充:首先,系统地探讨了乘客的构成及转化关系,并基于滞站乘客等车数、滞站原因及目的站距离提出一种处理滞站乘客乘车的方法,并以此方法计算滞站乘客等车的时间成本;其次,通过发车车型、模式和间隔的变量组合构建发车时刻表,进而以此表的信息为基础推算运营时刻表的各项变量,从而计算出公交服务各项指标及乘客和车辆的相关成本;最后,根据问题特征,应用最大最小蚁群系统算法求解模型。结合实例,对比分析了给定配车数和限定时间段内4种调度策略的发车时刻表最优解及相应最优解的公交服务指标和相关成本。实验结果表明,采用间隔不定的组合调度策略能够使车辆均衡分配站点客流,最大限度地降低乘客的时间成本及车辆耗燃成本。

关键词: 组合调度,大站快车,蚁群算法,发车时刻表,发车间隔

Abstract: Aiming at the shortage of the classification of passengers and handling method of stranded passengers in the single line transit mixed model with express bus,this paper supplemented the model by three steps.Firstly,the composition and transformation of the passengers were systematically discussed,meanwhile,a method based on the bus quantity of stranded passenger waiting for,stranded reason and the distance of destination station was put forward to deal with the stranded passenger distribution,and the time cost of the stranded passengers was calculated by this method.Secondly,the departure timetable was established with the combination of three variables-vehicle type,departure mode and headway,and then the variables of operating timetable were calculated based on this departure timetable information,and next the bus services indicators,passenger and vehicle related costs were also calculated.Finally,according to the characteristics of the problem,the max-min ant colony system algorithm was used to solve the model.With a given number of vehicles and a period of time,a comparative experiment was taken to analyze the optimal timetable solution of four scheduling strategies and its corresponding optimal solution’s bus service levels and total system cost.The experimental results demonstrate that the proposed model balances the passenger flow,and minimizes the cost of passenger time and vehicle fuel consumption.

Key words: Combination scheduling,Express bus,Ant colony algorithm,Departure timetable,Departure interval

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