Extended Great Deluge Meta-heuristic for the Integrated Dynamic Berth Allocation and Mobile Crane Assignment Problem

Abstract

In order for terminals to accommodate the growth in International container transport, they must make significant changes to maintain their position with increasing demand. One important manner in which existing terminal capacity could be increased would be through  more efficiency. In this paper, we consider terminal efficiency from the perspective of simultaneously improving both berth and quay crane scheduling. The approach is applied to a discrete and dynamic berth allocation and crane assignment problem for both mono-objective and multi-objective variants. The problem is solved through a neighborhood meta-heuristic called the Extended Great Deluge (EGD) . The results obtained with this meta-heuristic have shown better results than a Genetic Algorithm proposed in other works. A Simulated Annealing algorithm (SA) is also implemented to serve as basis of comparison for new instances results.