Planning for remarshaling in an automated container terminal using cooperative coevolutionary algorithms

The productivity of a container terminal is highly dependent on the efficiency of loading the containers onto the vessels. The efficiency of container loading depends on how the containers are stacked in the storage yard. Remarshaling refers to the preparatory task of rearranging the containers to maximize the efficiency of loading. In this paper, we propose cooperative coevolutionary algorithms (CCEAs) to derive a plan for remarshaling in an automated container terminal. CCEAs efficiently search for a solution in a reduced search space by decomposing a problem into subproblems. Our CCEA decomposes the problem into two subproblems: one for determining where to move the containers and the other for determining the movement priority. Simulation experiments show that our CCEA can derive a better plan in terms of the efficiency of both loading and remarshaling than other methods which are not based on the notion of problem decomposition.