Modeling And Optimization For Berth Allocation And Quay Crane Scheduling System

Container terminal plays an important strategic role in international logistics and national economies. It's an important node in international logistics. During the last four decades the container as an essential part of a unitload-concept has achieved undoubted importance in international sea freight transportation. With ever increasing containerization,the number of seaport container terminals and competition among them have become quite remarkable. Operations are nowadays unthinkable without effective and efficient use of information technology as well as optimization methods.The most important performance measure to a shipping line in rating a terminal is the vessel turnaround time (the average time the terminal takes to unload and load a docked vessel). From a customer's perspective, this measure is a cost measure that should be minimized. Another closely related measure that shipping lines use in choosing a terminal is the average quay crane rate, the quay cranes'throughput during a period, (total number of containers unloaded or loaded)/(total number of hours the quay crane operated). For a shipping line, this is a profit measure that should be maximized. Shipping lines judge container terminals largely based on vessel turnaround time and quay crane rate. All the decision problems we studied during this paper contributed to improving these measures. In the above context, this thesis utilizes many kinds of discipline theory and method, such as operation research, optimization theory and method, computer simulation and so on. Following the theory and practical experience of specialists, we research the berth allocation and quay crane scheduling problem.This thesis achieves the following results:1. Introducing the significance of this topic, the domestic and foreign research present situation. Explaining the operation process of the container terminals.2. Describing a nonlinear model for the berth allocation problem to minimize the turnaround time of containerships and considering the constraint with service priority.3. Improving the quay crane scheduling model with the constraint of quay cranes which different in the ability of handling containers. Optimizing the problem by minimize the total waiting time caused by quay cranes.4. Introducing two hybrid optimization strategies GASA and GATS and solving two models by them respectively. We develop procedures for each example and compare the simulation results to the results obtained by the traditional GA.