Number Of Reshuffles Research Articles

The impact of incomplete vessel arrival information on container stacking

Container stacking determines the incoming containers’ exact locations in a terminal storage yard which matters to the competitiveness of a port. The uncertain stacking or arrival sequence of containers caused by uncertain vessel arrival information brings some new challenges to container stacking. Based on the perspective of uncertainty, this article uses heuristic algorithms to evaluate the use of vessel arrival information to reduce the number of reshuffles, which differs from previous research mainly in the following three aspects: firstly, three different stacking principles i.e. the least reshuffle principle, lowest stack principle and nearest stack principle, are combined to create five new heuristics. Secondly, the incomplete information is divided into little, moderate and high levels and a variety of scenarios with different levels of vessel arrival information are generated to explore the effect of incomplete information on container stacking. Lastly, numerical experiments demonstrate that the results for complete information are presented to provide a lower bound reference. Moreover, the results obtained by different heuristics under different levels of vessel arrival information are closely related to factors like the bay scale, the bay utilisation rate and the number of containers.

Modelling and optimisation of online container stacking with operational constraints

ABSTRACTContainer transportation plays a critical role in the global shipping network and container terminals need to improve their operations to increase efficiency. Storage yard of a container terminal is a temporary area where the containers stay until they are shipped to their next destination. We concentrate on increasing the efficiency of the storage yard by developing online stacking policies for each incoming container. An unproductive move of a container, performed to reach another container stored underneath, is called reshuffling. The objective in container stacking problem is to minimise the number of reshuffles, thereby increasing the efficiency of terminal operations. Additional weight-related operational constraints bring additional complexity to the online stacking decisions. We propose a mathematical model for the optimal online assignment of an incoming export, transit, import or empty container. We also propose an optimal online stacking policy and compare it with a random policy through simulation. Additionally, lower bounds for the performance measures are obtained through simulation by relaxing the operational constraints of the problem in a third stacking policy. We present and discuss the computational results in terms of four main performance measures.

Simulation-based analysis for hierarchical storage assignment policies in a container terminal

This paper describes the structure and employment of a discrete-event simulation model for the real-life detailed processes performed during the handling of import containers. In particular, the model focuses on the storage assignment problem at the operational level in a container terminal with a multiple-berth structure. A novel approach using a hierarchical structure is adapted to partition the assignment problem into two sub-problems and solve each of them using separate decision rules. Suggested storage policies are evaluated in view of the overall performance of the container terminal. Different traffic densities are simulated to reflect the real-time environment. Simulation runs emphasize the bottleneck at the quay cranes. Results confirm that quay-crane efficiency may be improved by using appropriate storage policies. Strategies that adopted the integrated assignment method at the first level, where travel distances and gantry-crane workloads are considered, performed best at coping with this bottleneck. At the second level of the hierarchy, by using a segregated strategy, in which estimated container departure dates are considered, the number of reshuffles is reduced.