A Clonal Selection Algorithm for the container stacking problem

Due to increasing demand, container terminals face the challenges of increasing its service capacity and minimize the time of ships loading and unloading. The assignment of storage locations for reshuffled containers is a problem to the efficiency of container terminals operations, as a wrong assignment may result in several future reshuffles. This paper proposes a meta-heuristic based on the Clonal Selection Algorithm to minimize reshuffle when retrieving containers from a stack. The model competitiveness in accuracy and time are established by extensive numerical experiments comparing with an existing Integer Program model. The preliminary results obtained here suggest the proposed model is a promising optimization tool for the container stacking problem.