Real-time policy for yard allocation of transshipment containers in a terminal

In this article, we investigate the problem of allocating storage space in a container terminal's yard to transshipment containers. The main decision here concerns the block to which a container is assigned for storage until it is loaded later by another vessel. We propose a setting where some target performance measures are imposed on the discharge operations. In turn, the allocation decisions are made so as to reduce driving time from the storage blocks to the berth locations of the vessels that will pick up the containers. The trick here is to find an appropriate trade-off between the times spent on discharge and loading so that neither are delayed significantly. Using results from renewal theory, queuing theory and machine learning, we are able to quantify the effect of our allocation decisions on quay crane productivity. Thereafter, we formulate a mathematical optimization problem for the yard-allocation of containers and apply a meta-heuristic to solve it. Our method was developed for deployment by a software consultancy company for container terminals. We test our method using a real-time simulation and compare it with a benchmark from the literature. We show that our method generates reductions in vessel berth times and provide an overview on its economic impact.