Date of Award
Doctor of Philosophy in Transportation - (Ph.D.)
Executive Committee for the Interdisciplinary Program in Transportation
Athanassios K. Bladikas
I-Jy Steven Chien
As world container volume continues to grow and the introduction of 12,000 TEUs plus containerships into major trade routes, the port industry is under pressure to deal with the ever increasing freight volume. Gate congestion at marine container terminal is considered a major issue facing truckers who come to the terminal for container pickup and delivery. Harbor truckers operate in a very competitive environment; they are paid by trip, not by the hours they drive. Gate congestion is not only detrimental to their economic well-being, but also causes environmental pollution.
This thesis applies a multi-server queuing model to analyze marine terminal gate congestion and quantify truck waiting cost. In addition, an optimization model is developed to minimize gate system cost. Extensive data collection includes field observations and online camera observation and terminal day-to-day operation records. Comprehensive data analysis provides a solid foundation to support the development of the optimization model. The queuing analysis indicates that there is a substantial truck waiting cost incurred during peak season. Three optimization alternatives are explored. The results prove that optimization by appointment is the most effective way to reduce gate congestion and improve system efficiency. Lastly, it is the recommendation to use the combination of optimization by appointment and productivity improvement to mitigate terminal gate congestion and accommodate the ever growing container volume.
Guan, Chang Qian, "Analysis of marine container terminal gate congestion, truck waiting cost, and system optimization" (2009). Dissertations. 902.