Study of Coordinated Scheduling and Optimization Based on Public Transport Hub
The optimization method of regional scheduling based on the hub point in transit network is proposed by analyzing the current public transport scheduling problems and the development trend of regional transit. Through the set of the network edge and node property value, the highest number of bus line reaching node at the same time within the permissible error is the objective function; heuristic algorithm is used to solve the departure time and the time in station at each node of frequency for each line. Because all lines coordinated arriving, the transfer time of lines running on the network for passengers decreases. The total transfer cost of main nodes is reduced to achieve the transfer optimization of lines in the public transport network.
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Availability:
- Find a library where document is available. Order URL: http://worldcat.org/isbn/9780784411773
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Supplemental Notes:
- Copyright © 2011 ASCE
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Corporate Authors:
American Society of Civil Engineers
1801 Alexander Bell Drive
Reston, VA United States 20191-4400 -
Authors:
- Chen, Yan-yan
- Tian, Qi-hua
- Zhang, Guang-hou
- Wu, De-cang
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Conference:
- First International Conference on Transportation Information and Safety (ICTIS)
- Location: Wuhan , China
- Date: 2011-6-30 to 2011-7-2
- Publication Date: 2011
Language
- English
Media Info
- Media Type: Digital/other
- Features: Figures; References; Tables;
- Pagination: pp 1399-1405
- Monograph Title: ICTIS 2011: Multimodal Approach to Sustained Transportation System Development: Information, Technology, Implementation
Subject/Index Terms
- TRT Terms: Bus transit; Departure time; Dwell time; Genetic algorithms; Heuristic methods; Network nodes; Optimization; Scheduling
- Subject Areas: Data and Information Technology; Operations and Traffic Management; Public Transportation; I70: Traffic and Transport;
Filing Info
- Accession Number: 01450607
- Record Type: Publication
- ISBN: 9780784411773
- Files: TLIB, TRIS, ASCE
- Created Date: Oct 31 2012 9:20AM