Robust Optimization for Dynamic Traffic Assignment Under Demand Uncertainty.

Author(s)
Yao, T. Ben-Tal, A. Chung, B.D. & Mandala, S.
Year
Abstract

This paper considers operation and planning of surface transportation networks in an uncertain environment. A Cell Transmission Model (CTM) with a system optimal objective is used to model traffic dynamics. In particular,we focus on demand uncertainty residing in an appropriate uncertainty setsuch as box or polyhedral uncertainty set. We formulated an Affinely Adjustable Robust Counterpart (AARC) based linear programming model to study the multi-period transportation planning and operating problem. Simulation experiments show that the AARC solution provides excellent results when compared to Robust Counterpart(RC) solution and sampling based stochastic programming solution.

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Publication

Library number
C 48195 (In: C 47949 DVD) /70 / ITRD E854527
Source

In: Compendium of papers DVD 89th Annual Meeting of the Transportation Research Board TRB, Washington, D.C., January 10-14, 2010, 25 p.

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This publication is one of our other publications, and part of our extensive collection of road safety literature, that also includes the SWOV publications.