Improving crane routes in automated container terminals: a complex network approach

Abstract

The storage yard plays a key role in automated container terminals. This paper aims to shed new light on the planning of yard operations through the use of graph theory. Although complex graphs can be a very useful tool for planning yard operations, previous research has not addressed this issue yet. Given a theoretical representation of the storage yard as a small world model (Kleinberg's model), it is proposed a two-step method to improve crane routes on the yard. In the first step, a cluster detection technique is used to reveal the well-connected groups of nodes (ground slots). In the second step the crucial transition nodes between the groups are determined (bridge nodes). This study suggests that the terminal could gain efficiency in the long term by focusing on groups and bridge nodes.