Abstract
A robust optimization model is presented for the dynamic traffic assignment-based continuous network design problem, which accounts for a bilevel objective and long-term origin-destination demand uncertainty. The model also embeds Daganzo's cell transmission model. The objective minimizes the trade-off between expected total system travel time (TSTT) and expected risk. As such, the robust model provides the optimal solution that is least sensitive to the variation of travel demand, given the degree of robustness by transportation planners. The new robust model is compared with the existing network design models on a simple cell transmission test network. The robust model with greater degree of robustness yields less expected risk with the sacrifice of higher expected TSTT. The robust model yields the most robust solution, and no other model provides a satisfactory solution across the budget range. In addition, how a visualized graph may be used to elicit the preference information from transportation planners on the desired degree of robustness is illustrated.
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