Transport Network Design Problem under Uncertainty: A Review and New Developments

Anthony Chen, Zhong Zhou, Piya Chootinan, Seungkyu Ryu, Chao Yang, S. C. Wong

Research output: Journal article publicationReview articleAcademic researchpeer-review

90 Citations (Scopus)


This paper aims to provide a state-of-the-art review of the transport network design problem (NDP) under uncertainty and to present some new developments on a bi-objective-reliable NDP (BORNDP) model that explicitly optimizes the capacity reliability and travel time reliability under demand uncertainty. Both are useful performance measures that can describe the supply-side reliability and demand-side reliability of a road network. A simulation-based multi-objective genetic algorithm solution procedure, which consists of a traffic assignment algorithm, a genetic algorithm, a Pareto filter, and a Monte-Carlo simulation, is developed to solve the proposed BORNDP model. A numerical example based on the capacity enhancement problem is presented to demonstrate the tradeoff between capacity reliability and travel time reliability in the NDP.
Original languageEnglish
Pages (from-to)743-768
Number of pages26
JournalTransport Reviews
Issue number6
Publication statusPublished - 1 Nov 2011
Externally publishedYes

ASJC Scopus subject areas

  • Transportation

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