Design, analysis, and real -time control of seaport container transshipment terminals.

Abstract

In Chapter 1, we present a state-of-the-art discrete event simulation model of operations inside seaport container transshipment terminals. This model, based on the author's internship and extended on-site experience at a major container terminal in Asia, is the first model in the literature to directly connect (1) terminal design options and (2) real-time yard control algorithms to the overall productivity (i.e. long-run gross crane rate) at a seaport container terminal. Regarding terminal design, we present several new results on yard layout, yard crane and yard truck fleet composition, terminal capacity, and other problems. Regarding real-time control, we present several new results on real-time container storage and retrieval location assignment; real-time inter-zone yard crane deployment; real-time intra-zone yard crane dispatching; and real-time dual-load truck dispatching. In all experiments, performance is measured according to the industry standard metric. The quick runtime of the simulation model demonstrates that the proposed algorithms are suitable for deployment even at the world's largest container terminals. These findings have the potential to significantly improve the productivity of container terminals around the world. In Chapter 2, we introduce and analyze a serial material handling system in which items are transported through a sequence of stations from an origin to a destination via a series of vehicles that move back and forth between consecutive stations. Each pair of consecutive stations is connected by a single vehicle with unit capacity that travels back and forth between the upstream and downstream stations. Vehicles travel with items in the downstream direction and without items in the upstream direction. Stations act as holding areas for items awaiting further transport within the system. Stations may have non-identical capacities. We model this system as a continuous time Markov chain and develop a recursive algorithm for generating the state transition matrix for any system configuration. After solving for the steady state probabilities using the Gauss-Seidel method, we compute the average throughput rate, average number of items in the system, and average sojourn time for various system configurations.