Identifying Critical Links in Transportation Network Design Problems for Maximizing Network Accessibility

Yufeng Zhang, Alireza Khani

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

A significant amount of research has been performed on network accessibility evaluation, but studies on incorporating accessibility maximization into network design problems have been relatively scarce. This study aimed to bridge the gap by proposing an integer programming model that explicitly maximizes the number of accessible opportunities within a given travel time budget. We adopted the Lagrangian relaxation method for decomposing the main problem into three subproblems that can be solved more efficiently using dynamic programming. The proposed method was applied to several case studies, which identified critical links for maximizing network accessibility with limited construction budget, and also illustrated the accuracy and efficiency of the algorithm. This method is promisingly scalable as a solution algorithm for large-scale accessibility-oriented network design problems.

Original languageEnglish (US)
Pages (from-to)237-251
Number of pages15
JournalTransportation Research Record
Volume2674
Issue number2
DOIs
StatePublished - Feb 2020

Bibliographical note

Funding Information:
The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This research was conducted at the University of Minnesota Transit Lab, currently supported by the following, but not limited to, sponsors: the National Science Foundation: awards CMMI-1637548 and CMMI-1831140, the Freight Mobility Research Institute (FMRI), TIER 1 Transportation Center, U.S. Department of Transportation: award RR-K78/FAU SP#16-532 AM2, the Minnesota Department of Transportation: Contract 1003325 WO 111, 1003325 WO 15, and 1003325 WO 44, and the Transitways Research Impact Program (TIRP): Contract A100460 WO UM2917.

Publisher Copyright:
© National Academy of Sciences: Transportation Research Board 2020.

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