Building Agent-Based Models of Seaport Container Terminals

Agent-based models are increasingly being used to simulate and analyze various transportation problems, from traffic flow [15] to air traffic control [1]. One transportation industry that has not received as much attention from the multi-agent systems community is seaport container terminals. It can be argued that the operations that take place at a container terminal are as complex as that of an airport. A seaport container terminal faces a myriad of operational challenges such as optimizing berth space, minimizing ship turnaround time, maximizing use of resources, and reducing wait time of drayage trucks. Due to environmental concerns, terminal operators and port planners are focusing on the problem of reducing the in-terminal wait time of drayage trucks. In this paper, we present our multiagent model of a container yard operation, its implementation using NetLogo, and some initial test results. We model yard cranes as opportunistic utility-maximizing agents using several different utility functions for comparison purposes. By using a representative layout of a terminal our simulation model allows us to analyze the behavior of the cranes and evaluate the collective performance of the system. We demonstrate that it is possible to build a realistic and useful model of yard crane operation. Our test results show that utility functions that give higher precedence to nearby trucks lead to much better results than those that favor serving trucks on a mostly first-come first-serve order.