Scope and Method of Study. Nowadays, commercial companies view transportation process as a part of the whole logistic concept. However, most existing freight transport models are still focused only on direct factors such as transport cost and transit time. In this thesis, an alternative way for freight transport modeling which also considers other important factors in the context of supply chain and logistics was explored. The proposed models are expected to increase accuracy and forecasting capability as well as address logistical considerations e.g. shipment size, use of distribution/consolidation centers and inventory aspects within the existing freight transport models. The first part of the thesis developed optimization models based on the clustering concept for classifying commodities into logistical families. The second part of the thesis includes a study of explanatory variables and the structure of discrete choice model for freight transport mode and route selection. In addition, the conventional mathematical model for stochastic user equilibrium assignment and the problems when applying such a model with the proposed utility function were analyzed. A heuristic approach for stochastic user equilibrium with the proposed utility function was developed and tested with a small intermodal network for multi OD pairs and multi commodity assignment.;Findings and Conclusions. For the first part of the thesis, the optimization models developed were applied to classify commodities into logistical families. The numerical experiments showed that the algorithms were flexible and effective in classifying commodities. For the second part, it was shown that the new utility function incorporating important supply chain and logistics variables made the conventional mathematical program for stochastic user equilibrium not equivalent to the flow pattern at the equilibrium point. As a result, a heuristic algorithm for stochastic user equilibrium assignment was developed and tested with multiple OD pairs/commodities and freight flow assignment was illustrated using a simplified intermodal network. Based on the numerical example, the proposed heuristic algorithm appears to function quite efficiently.
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