Abstract

Efficient freight transportation is essential for a strong economic system. Increases in demands for freight transportation, however, lessens the efficiency of existing infrastructure. In order to alleviate this problem effectively, evaluation studies must be performed in order to invest limited resources for maximum social benefits. In addition to many difficulties related to evaluating individual projects, complimentary and substitution effects that occur when considering transportation projects together must be properly accounted for. Current practices, however, limit the number of projects that can feasibly be considered at one time. This dissertation proposes network design models which can automatically create project combinations and search for the best of these. Network design models have been studied for the passenger movements and focus on highway expansions. In this dissertation, the focus is shifted to freight movements which involve multimodal transportation improvements. A freight network design model is developed based on a bi-level optimization model. The development then involves two components. The first task is to set the freight investment problems within the bi-level format. This includes finding a suitable freight flow prediction model which can work well with the bi-level model. The second task is to provide a solution algorithm to solve the problem. The dissertation sets the framework of the freight flow network design model, identifies expected model issues, and provides alternatives that alleviate them. Through a series of developments, the final model uses a shipper-carrier freight equilibrium model to represent freight behaviors. Capacity constraints are used as a means to control service limitations since reliability issues, an important factor for freight movements, cannot be captured by steady state traffic assignment. A case study is implemented to allocate a budget for improvements on the California highway network. The transportation modes are selected by the shipper model which can include truck, rail, or multimodal transportation. The results shown that the proposed network design model provides better solutions compared with traditional ranking methods. The solution algorithm can manage the problem with a reasonable number of project alternatives.