A mathematical programming formulation is developed to determine the throughput of a freight transportation network. The impact of demand and capacity uncertainty on the throughput is systematically studied. Mathematical proofs are provided to show that accounting for capacity uncertainty by using a single-point expected value can lead to systematic overestimation of network throughput. This result is also valid for other measures, such as system capacity. Two sampling-based methodologies–independent random number and common random number–are provided to determine network design decisions in the presence of demand uncertainty. The sampling-based solution methods provide an approximate estimate of optimal solution and provide probabilistic bounds on the optimality gap. The presented methodologies are generic and can be applied even if different functional forms (nonlinear, nonconvex) are used to model various aspects of the freight transportation network. The numerical tests demonstrate that not accounting for capacity uncertainty can result in overestimation of system throughput of up to 40%. A common random number-based sampling strategy was found to significantly outperform the independent random number strategy for all the scenarios tested.


    Access

    Download

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Freight Transportation Network Design Problem for Maximizing throughput under Uncertainty


    Additional title:

    Transportation Research Record: Journal of the Transportation Research Board


    Contributors:


    Publication date :

    2009-01-01




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English






    Relay network design in freight transportation systems

    Ali, Tarab H. | Online Contents | 2002


    Multimodal Freight Transportation Network Design Problem for Reduction of Greenhouse Gas Emissions

    Kim, Suhyeon / Park, Minchoul / Lee, Chungwon | Transportation Research Record | 2013