Dynamic congestion pricing with demand uncertainty: A robust optimization approach

Dynamic congestion pricing with demand uncertainty: A robust optimization approach

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Article ID: iaor20127869
Volume: 46
Issue: 10
Start Page Number: 1504
End Page Number: 1518
Publication Date: Dec 2012
Journal: Transportation Research Part B
Authors: , , ,
Keywords: programming: dynamic
Abstract:

In this paper, we consider dynamic congestion pricing in the presence of demand uncertainty. In particular, we apply a robust optimization (RO) approach based on a bi‐level cellular particle swarm optimization (BCPSO) to optimal congestion pricing problems when flows correspond to dynamic user equilibrium on the network of interest. Such a formulation is recognized as a second‐best pricing problem, and we refer to it as the dynamic optimal toll problem with equilibrium constraints (DOTPEC). We then present numerical experiments in which BCPSO is compared with two alternative robust dynamic solution approaches: bilevel simulated annealing (BSA) and cutting planebased simulated annealing (CPSA), as well as a nominal dynamic solution and a robust static solution. We show that robust dynamic solutions improve the worst case, average, and stability of total travel cost in comparison with the nominal dynamic and the robust static solutions. The numerical results also show that BCPSO outperforms BSA and CPSA in terms of solution quality and computational efficiency.

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