摘要: |
The complexity and dynamics of multimodal freight transportation together with the unpredictability of incidents, disruptions and demand changes make the optimum routing of freight a challenging task. Optimum routing decisions in a multimodal transportation rely on the estimation of the dynamical states of the multimodal traffic network. Such estimations rely on mathematical models that are often highly inaccurate leading to routing decisions that deviate considerably from optimality. In addition, they do not consider the impact of the routed freight on the states of the network. The purpose of this project is to use complex real time simulation models to estimate the states of the transportation network and integrate that information with optimization and load balancing techniques in an iterative feedback configuration that would lead to much more efficient routing decisions during normal operations and disruptions. The approach is referred to as the CO-SiMulation Optimization (COSMO) approach. We use a simulation testbed consisting of a road traffic simulation model and a rail simulation model for the Los Angeles/Long Beach Port area to demonstrate the efficiency of the proposed approach. The results demonstrate the potential of the approach for practical freight routing. |