American Society of Civil Engineers


Approximation Techniques for Transportation Network Design Problem under Demand Uncertainty


by Sushant Sharma, (Postdoctorate Research Associate, NEXTRANS, Regional Univ. Transportation Center, Purdue Univ., West Lafayette, IN. E-mail: sharma57@purdue.edu), Tom V. Mathew, (corresponding author), (Associate Professor, Transportation Systems Engineering, Dept. of Civil Engineering, Indian Institute of Technology Bombay, Powai, Mumbai-400 076, India E-mail: vmtom@civil.iitb.ac.in), and Satish V. Ukkusuri, (Associate Professor, School of Civil Engineering, Purdue Univ., West Lafayette, IN 47907. E-mail: sukkussur@purdue.edu)

Journal of Computing in Civil Engineering, Vol. 25, No. 4, July/August 2011, pp. 316-329, (doi:  http://dx.doi.org/10.1061/(ASCE)CP.1943-5487.0000091)

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Document type: Journal Paper
Abstract: Conventional transportation network design problems treat origin-destination (OD) demand as fixed, which may not be true in reality. Some recent studies model fluctuations in OD demand by considering the first and the second moment of the system travel time, resulting in stochastic and robust network design models, respectively. Both of these models need to solve the traffic equilibrium problem for a large number of demand samples and are therefore computationally intensive. In this paper, three efficient solution-approximation approaches are identified for addressing demand uncertainty by solving for a small sample size, reducing the computational effort without much compromise on the solution quality. The application and the performance of these alternative approaches are reported. The results from this study will help in deciding suitable approximation techniques for network design under demand uncertainty.


ASCE Subject Headings:
Uncertainty principles
Transportation networks
Sampling
Algorithms

Author Keywords:
Demand uncertainty
Transportation network design
Sampling techniques
Single-point approximation
Genetic algorithm