华南理工大学学报(自然科学版) ›› 2021, Vol. 49 ›› Issue (1): 123-133.doi: 10.12141/j.issn.1000-565X.200248

所属专题: 2021年交通运输工程

• 交通运输工程 • 上一篇    下一篇

基于混合算法的需求响应公交灵活调度模型

靳文舟1 胡为洋1 邓嘉怡1 罗晨伟2 韦兰辉2   

  1. 1. 华南理工大学 土木与交通学院,广东 广州 510640; 2. 广州市交通规划研究院,广东 广州 510230
  • 收稿日期:2020-05-18 修回日期:2020-07-29 出版日期:2021-01-25 发布日期:2021-01-01
  • 通信作者: 靳文舟 ( 1960-) ,男,教授,博士生导师,主要从事交通规划、公交线网优化研究。 E-mail:ctwzhjin@ scut.edu.cn
  • 作者简介:靳文舟 ( 1960-) ,男,教授,博士生导师,主要从事交通规划、公交线网优化研究。
  • 基金资助:

    国家自然科学基金资助项目 ( 52072128)

Flexible Scheduling Model of Demand Response Transit Based on Hybrid Algorithm

JIN Wenzhou1  HU Weiyang1  DENG Jiayi1  LUO Chenwei2  WEI Lanhui2   

  1. 1. School of Civil Engineering and Transportation,South China University of Technology,Guangzhou 510640,Guangdong,China; 2. Guangzhou Transport Planning Research Institute,Guangzhou 510230,Guangdong,China
  • Received:2020-05-18 Revised:2020-07-29 Online:2021-01-25 Published:2021-01-01
  • Contact: 靳文舟 ( 1960-) ,男,教授,博士生导师,主要从事交通规划、公交线网优化研究。 E-mail:ctwzhjin@ scut.edu.cn
  • About author:靳文舟 ( 1960-) ,男,教授,博士生导师,主要从事交通规划、公交线网优化研究。
  • Supported by:
    Supported by the National Natural Science Foundation of China ( 52072128)

摘要:

: 需求响应公交 ( DRT) 是一种新型的公共交通服务模式,为了使 DRT 理论能 更贴合实际应用于低密度人口地区,提出了考虑多种车型和多种运营模式的公交灵活调 度方式。首先设立车型和路径的双决策变量,并构建了考虑多种车型和多种运营模式的 公交灵活调度模型; 然后采用大循环小循环混合模式设计了混合遗传蚁群算法 HGACO, 该算法混合了最近邻搜索算法、2-opt 法、目的地降维算子、遗传算法和蚁群算法; 最 后以揭西南部部分地区至城中心的 3 个时段为例进行调度。结果显示: 考虑多种车型和 多种运营模式的公交灵活调度模型具有经济性和可操作性,该模型可以使低密度地区的 需求响应调度更加科学和经济; 改进的混合遗传蚁群算法 HGACO 的求解能力、精度和 稳定性均优于原算法,可以稳定地求得 DRT 灵活调度问题的较优解。

关键词: 需求响应公交, 灵活调度, 多车型, 多种运营模式, 混合遗传算法, 混合遗 传 - 蚁群算法

Abstract:

Demand response transit ( DRT) serves is a new type of public transportation service mode. In order to make DRT theory more suitable for practical application in low-density population areas,a flexible bus scheduling model considering multiple vehicle types and multiple operating modes was proposed. First,dual decision variables for vehicle type and route were set up,and then a flexible bus dispatch model that considers multiple vehicle types as well as multiple operating modes was built. Then,a hybrid genetic ant colony algorithm HGACO,which is composed of nearest neighbor search algorithm,2-opt method,destination dimensionality reduction operator,genetic algorithm and ant colony algorithm,was designed using the hybrid model of“large loop and small loop”. Finally, taking the three sections from the southwest part of the city to the city center as an example for scheduling,the results show that the flexible bus dispatch model considering the multi-vehicle and multi-ple operation mode is practical and operable,and it can make DRT in low-density areas more scientific and economical. The improved hybrid algorithm HGACO is superior to the original algorithm in solution ability,accuracy and stability,and can stably obtain a better solution to the DRT flexible scheduling problem.

Key words: demand response transit, flexible scheduling, multiple models, multiple operation modes, hybrid genetic algorithm, hybrid genetic ant colony algorithm

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