A Parallel Ant Colony Algorithm for Bus Network Optimization

This paper presents an optimization model for a bus network design based on the coarse-grain parallel ant colony algorithm (CPACA). It aims to maximize the number of direct travelers/unit length; that is, direct traveler density, subject to route length and nonlinear rate constraints (ratio of the length of a route to the shortest road distance between origin and destination). CPACA is a new optimal algorithm that 1) develops a new strategy to update the increased pheromone, called Ant-Weight, by which the path-searching activities of ants are adjusted based on the objective function, and 2) uses parallelization strategies of an ant colony algorithm (ACA) to improve the calculation time and the quality of the optimization. Data collected in Dalian City, China, is used to test the model and the algorithm. Results show that the optimized bus network has significantly reduced transfers and travel time. The data also reveals that the proposed CPACA is effective and efficient compared to some existing ant algorithms.

Availability:
- Find a library where document is available. Order URL: http://worldcat.org/issn/10939687
Authors:
- Yang, Zhongzhen
- Yu, Bin
- Cheng, Chuntian
Publication Date: 2007-1

Language

English

Media Info

Media Type: Print
Features: Figures; References; Tables;
Pagination: pp 44-55
Serial:
- Computer-Aided Civil and Infrastructure Engineering
- Volume: 22
- Issue Number: 1
- Publisher: Blackwell Publishing
- ISSN: 1093-9687
- Serial URL: http://onlinelibrary.wiley.com/journal/10.1111/(ISSN)1467-8667

Subject/Index Terms

TRT Terms: Algorithms; Bus routes; Bus transit operations; Origin and destination; Travel time; Urban transit
Uncontrolled Terms: Ant colony optimization
Geographic Terms: Dalian (China)
Subject Areas: Operations and Traffic Management; Public Transportation;

Filing Info

Accession Number: 01042289
Record Type: Publication
Files: TRIS
Created Date: Feb 24 2007 11:53PM