Freight and freightage

The Freight Mobility Research Institute’s (FMRI) contribution focuses on promoting smart cities, improving multimodal connections, system integrations and security, data modeling, and analytical tools. The ultimate goal of the FMRI is to optimize freight movements for improving the overall freight transportation efficiency. The FMRI's mission is to address critical issues affecting planning, design, operation, and safety of the nation’s intermodal freight transportation systems, in order to strengthen nation’s
economic competitiveness.

Lately, the attractiveness of cities has contributed to a rise in vehicle movements to and from cities. The growth of freight movements in cities predictably will be one of the critical issues of the near future. Congestion caused by the increased movements of freight impacts the flow of private and transit vehicles. Thus, it is crucial to reduce the congestion on multimodal corridors. Components of the Intelligent Transportation System (ITS) such as Freight Signal Priority (FSP) and Transit Signal Priority (TSP) that promote the freight and transit vehicles may not only help solve these conditions but may assist with the sustainability of the system. The primary objective of this research is to develop guidelines for traffic agencies to implement signal priorities based on identified decision factors on certain corridors. Besides, this study evaluates the efficiency of FSP and TSP in improving the performance of freight and transit systems. Finally, inclusive guidelines are drawn up based on the literature and the conducted simulation. The developed guidelines apply to corridors where freight delay plays a vital role in the assessment of corridor benefits.

Ports and container terminals have very complex and dynamic operations. Effective and efficient berth schedules are essential for profitable and sustainable operations. This research studies berth scheduling under uncertainties in arrival and handling times. Port operators usually face challenges in the development of berth schedules. This thesis presents a model formulation of discrete berth space that accounts for uncertainty in arrival and handling times. The problem is reformulated as a biobjective bi-level optimization berth scheduling problem. A solution approach is presented using evolutionary algorithms and heuristics. The objective of the formulation is to provide a robust berth schedule by minimizing the average and the range of the total service times for all vessels served at the terminal. Simulation is utilized to evaluate the proposed berth scheduling policy and compare it to two first-come-first-served policies. Results showed that the proposed berth schedules outperform under high congestion.

With congestion, environmental Impact, and the price of oil becoming topics that influence businesses and individuals in a daily basis, measures need to be undertaken in order to accommodate the growing demand for freight transportation. By directing many of the trucks travelling along the National Highways Systems to the Marine Highway corridors developed by the U.S. Maritime Administrations, many of the problems can be addressed in the Short and Medium terms. In order to do so, Short Sea Shipping, through the use of Ro/Ro (Roll-on/Roll-off) Vessels, needs to be implemented. Although the environmental and congestion reducing benefits are considerable, the profitability of this transportation mode needs to be considered. A cost benefit analysis can determine the margin of profit, and attract investors and businesses. By developing a mathematical model that accounts the costs associated with transporting trucks along a particular corridor, the competitiveness of Short Sea Shipping can be determined.

In recent years, there has been an exponential increase in container volume shipment within intermodal transportation systems. Container terminals as part of the global port system represent important hubs within this intermodal transportation system. Thus, the need to improve the operational efficiency is the most important issue for container terminals from an economic standpoint. Moreover, intermodal transportation systems, ports and inland transport facilities should all be integrated into one coordinated plan. More specifically, a method to schedule different types of handling equipment in an integrated way within a container terminal is a popular topic for researchers. However, not many researchers have addresses this topic in relationship to the simulation aspect which will test feasible solutions under real container terminal environment parameters. In order to increase the efficiency of operations, the development of mathematical models and algorithms is critical in finding the best feasible solution. The objective of this study is to evaluate the feasible solution to find the proper number of Yard Trailers (YTs) with the minimal cost for the container terminals. This study uses the Dynamic YTs operation's method as a background for modeling. A mathematical model with various constraints related to the integrated operations among the different types of handling equipment is formulated. This model takes into consideration both serving time of quay cranes and yard cranes, and cost reduction strategies by decreasing use of YTs with the specific objective of minimum total cost including utilization of YTs and vessel berthing. In addition, a heuristic algorithm combined with Monte Carlo Method and Brute-Force Search are employed. The early Stage Technique of Monte Carlo method is proposed to generate vast random numbers to replicate simulation for real cases.