Coordinated optimization of equipment operations on a container terminal

Gecoordineerde optimalisatie van machine operaties op een container terminal

More Info
expand_more

Abstract

Increased international marine transport has increased the use of containers. This goes hand in hand with the increased demand for well-functioning container terminals. The speed at which containers can be handled on the container terminal is an important performance indicator for container terminals. In particular, the productivity of the Quay Crane (QC)s is used to determine the performance of a container terminal. To achieve a high performance, a well designed schedule of operations is required. This research investigates to what extent a coordinated planning can contribute to increasing the QC productivity. Currently, an uncoordinated scheduling heuristic is used to dispatch the equipment operating on a container terminal. With a coordinated schedule, operations of all equipment working on the terminal can be considered at once to achieve optimal QC productivity. A Hybrid Flow Shop (HFS) model with revolutionary features is used to model the waterside of a container terminal in a coordinated way. The revolutionary features are called: bi-directional and job-pairs. The former enables jobs to move through the HFS in both directions, the latter constrains certain jobs to be performed simultaneously by a single machine. Subsequently, a tailored Simulated Annealing (SA) algorithm is used to obtain a heuristic solution to this mathematical model. The performance of the HFS model in combination with the SA algorithm is evaluated with a sophisticated and validated container terminal simulation model developed by TBA. Therefore, the SA algorithm should balance between both quality and computational time. Computational time should not be excessive since the schedule has to be adjusted frequently since operations on a container terminal vary quickly and predictions with regards to processing times are unreliable. To evaluate the performance of the coordinated schedule, it will be compared with the uncoordinated scheduling heuristic of TBA. Based on the results obtained during this research, the QC productivity whilst using TBA's uncoordinated scheduling heuristic cannot be increased with a coordinated schedule that uses a HFS to model the container terminal and a SA algorithm to solve that model (p-value 0.2731). On the other hand, it can neither be concluded that TBA's uncoordinated scheduling heuristic results in higher productivity compared to the coordinated schedule. Therefore, the coordinated schedule is a solid alternative to TBA's uncoordinated scheduling heuristic. However, it is expected that with certain changes to the coordinated schedule the QC productivity could be increased.