Optimization of Transportation Networks for Freight, Based on Costs, Network Robustness and Environmental Impact

Abstract

The strategic analysis and planning of investments on transportation infrastructure is something that inherently has a long term horizon and, as such, should be carefully studied and thought through. This PhD project addresses the problem of how to best optimize the investments made on a transportation network in order to minimize the transportation costs and environmental impacts of freight transportation, and to maximize the transportation network robustness. The long term nature of this kind of analysis means that some factors and parameters that today assume a certain value, may change quite significantly in the long run. Due to that, the best possible investment scenario will likely vary according to the values of the parameters used, which means that the developed model has to be able to accommodate for various key parameter values, and multiple future scenarios. The goal of this PhD project is to develop a strategic freight transportation network optimization model that weights in several different factors and is flexible enough to accommodate for possible changes in key factors, so that it can be used as an important tool in planning investments for new and improved transportation infrastructures. After having completed the needed literature review step, the following objectives are expected to be accomplished under this PhD project: The first objective is to develop a strategic freight transportation traffic assignment model, capable of assigning freight traffic to a network, in which the freight movements (O/D - Origin/Destination - tables) and the transportation costs for each type of movement are introduced by the user. Due to its macro nature, the model will not consider congestion, but will take capacity limits into account and assume a stochastic component in modal choice. The second objective is to conceive a freight network optimization model, which, based on the developed freight transportation model, and using factors such as costs and environmental impact to evaluate each scenario, is able to find an optimal (or close to optimal) way in which to invest a specific volume of capital on a transportation network. The third objective is to apply the network optimization model to several artificial networks in an effort to understand if there is a pattern in the way transportation investments should be made. To finalize, the forth objective is to perform a case study, by applying the proposed model to a real world network and analyzing the results.