Surrogate-Based Optimization of Expensive-to-Evaluate Objective for Optimal Highway Toll Charges in Transportation Network

Applying the optimized pricing scheme in the real world can be an encouraging policy option to enhance the performance of the transportation system in the study region. A family of surrogate-based optimization approaches to approximate the response surface for the transportation simulation input-output mapping is adopted in this article. These approaches search for the optimal toll charges in a transportation network and the computational effort can be significantly reduced for the expensive-to-evaluate optimization problem. Meanwhile, this family of approaches addressed the random noise that always occurs through simulations. Both one-stage and two-stage surrogate models are tested and compared and a suboptimal exploration strategy and a global exploration strategy are incorporated and validated. Dynamic Urban Systems in Transportation (DynusT), a simulation-based dynamic traffic assignment model, is utilized to evaluate the system performance in response to different link-additive toll schemes implemented on a highway in a real road transportation network. The simulation results show that implementing the optimal toll predicted by the surrogate model can benefit society in multiple ways by minimizing travel time. Travelers gain from the 2.5% reduction (0.45 minutes) of the average travel time and the total reduction in the time cost during the extended peak hours would be around $65,000 for all of the 570,000 network users. The article discusses how the government benefits from the 20% increase of toll revenue compared to the current situation.


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  • Accession Number: 01525629
  • Record Type: Publication
  • Files: TRIS
  • Created Date: Apr 30 2014 10:26AM