Traffic & Transportation Engineering

Flexible Scheduling Model of Demand Response Transit Based on Hybrid Algorithm

Expand
  • 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
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。

Received date: 2020-05-18

  Revised date: 2020-07-29

  Online published: 2021-01-01

Supported by

Supported by the National Natural Science Foundation of China ( 52072128)

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.

Cite this article

JIN Wenzhou, HU Weiyang, DENG Jiayi, et al . Flexible Scheduling Model of Demand Response Transit Based on Hybrid Algorithm[J]. Journal of South China University of Technology(Natural Science), 2021 , 49(1) : 123 -133 . DOI: 10.12141/j.issn.1000-565X.200248

Outlines

/