Containerization

Intermodal facilities, including port operations, play a significant role in the economic framework of the United States by making substantial contributions to the country's GDP, but face challenges managing increased freight volumes. However, increased transportation time within port facilities leads to higher costs, emissions, and impacts on efficiency and sustainability. This thesis aims to develop a concept of operations (ConOps) for improving the efficiency of heavy truck movement outside ports, with goals of reducing congestion, considering greenhouse gas (GHG) emissions, and addressing issues faced by the truck drivers. The study proposes integrating technological solutions to streamline heavy truck traffic at intermodal port facilities, including scheduled truck arrivals and departures, truck stop and rest areas near ports, real-time traffic information, implementation of dedicated truck lanes, and autonomous truck platooning. The focus is improving communication, efficiency, and safety for trucking companies, operations managers, and truck drivers. Using microsimulation modeling in PTV VISSIM (2023), a traffic impact study is also conducted, focusing on a case study near the Port of Miami. A base scenario is developed to represent current traffic conditions, and additional scenarios are implemented to evaluate different strategies, such as dedicated and exclusive truck lanes, freeway lane restrictions, and autonomous truck platooning. Simulation findings emphasize the positive impact of these strategies on travel times and delays, and forecast scenarios account for increased truck volumes. Dedicated truck lanes and truck platooning demonstrate promising results in reducing congestion and improving overall traffic flow. This research supports decision-making for government officials and logistics service providers in sustainable and efficient intermodal freight planning. The study also suggests opportunities for future extensions, including emerging technologies and tailored solutions for different port locations and contexts.

Over the last thirty years, intermodal freight transportation has been a constantly expanding sector. The vast increase of freight volumes contributes to the increase of various issues in the freight corridors as well as the urban environment. The deterioration of congestion in the urban environment and the increase on freight movements on the highways have resulted in the increase of emissions. For this reason, new policies and regulations are put forth to address the environmental effects of freight transportation. This study deals with the intermodal freight network design problem from the shipping company's perspective, aiming to simultaneously minimize emission levels and cost of freight transportation. We propose a mathematical model for optimizing the design of an intermodal freight network and the location of intermodal hubs between the origins and the destinations, under delivery time constraints. The goal is to identify the mode choice patterns considering transport cost and emissions, and the effects of new emission regulations on network costs. We consider a network with marine terminals as the origins, inland intermodal terminals as the hubs, and fulfillment centers as the destinations. Numerical experiments highlight that the proposed model can provide useful insights to the shipper.

The study of the reusable container inventory control in a distribution network is crucial to the efficiency and cost effectiveness of the transportation systems. In order to minimize the total operation cost of such a transportation network system, all subsystems of the distribution network have to be optimized together as a whole system. In this study, we extended the inventory control concept and developed a multiple-inventory control model for the transportation network. We presented a systematic approach to address all those subsystems as interrelated systems. Mathematical models were developed for the transportation and container inventory control problems first. Then, the statistical modeling method was used to analyze the effects of the container inventory management policies on the performance of the transportation system. Based on the optimization theory, simulation executions were such arranged to lead to the globe optimality. This makes it possible to optimize the variables of inventory control under different control policies without solving mathematical models. A Simulation Code Generator (SCG) was also developed for a general container inventory control system.