Trip Assignment Model for Timed-Transfer Transit Systems
Abstract
Get full access to this article
View all access and purchase options for this article.
References
Cite article
Cite article
Cite article
Download to reference manager
If you have citation software installed, you can download article citation data to the citation manager of your choice
Information, rights and permissions
Information
Published In

Authors
Metrics and citations
Metrics
Journals metrics
This article was published in Transportation Research Record: Journal of the Transportation Research Board.
VIEW ALL JOURNAL METRICSArticle usage*
Total views and downloads: 10
*Article usage tracking started in December 2016
Altmetric
See the impact this article is making through the number of times it’s been read, and the Altmetric Score.
Learn more about the Altmetric Scores
Articles citing this one
Receive email alerts when this article is cited
Web of Science: 0
Crossref: 10
- Cooperatively coevolutionary optimization design of limited-stop servi...
- Urban transit network optimization under variable demand with single a...
- A multi-objective meta-heuristic approach for the transit network desi...
- A simultaneous transit network design and frequency setting: Computing...
- Efficiency Evaluation of Urban Transit Terminals Based on the Cloud Mo...
- Using a Simulated Annealing Algorithm to Solve the Transit Route Netwo...
- Optimal Transit Route Network Design Problem with Variable Transit Dem...
- Bus dispatching at timed transfer transit stations using bus tracking ...
- Planning and Design Model for Transit Route Networks with Coordinated ...
- A Tabu Search Based Heuristic Method for the Transit Route Network Des...
Figures and tables
Figures & Media
Tables
View Options
Get access
Access options
If you have access to journal content via a personal subscription, university, library, employer or society, select from the options below:
loading institutional access options
Alternatively, view purchase options below:
Purchase 24 hour online access to view and download content.
Access journal content via a DeepDyve subscription or find out more about this option.
