Combined quay crane assignment and quay crane scheduling with crane inter-vessel movement and non-interference constraints

Integrated models of the quay crane assignment problem (QCAP) and the quay crane scheduling problem (QCSP) exist. However, they have shortcomings in that some do not allow movement of quay cranes between vessels, others do not take into account precedence relationships between tasks, and yet others do not avoid interference between quay cranes. Here, an integrated and comprehensive optimization model that combines the two distinct QCAP and QCSP problems which deals with the issues raised is put forward. The model is of the mixed-integer programming type with the objective being to minimize the difference between tardiness cost and earliness income based on finishing time and requested departure time for a vessel. Because of the extent of the model and the potential for even small problems to lead to large instances, exact methods can be prohibitive in computational time. For this reason an adapted genetic algorithm (GA) is implemented to cope with this computational burden. Experimental results obtained with branch-and-cut as implemented in CPLEX and GA for small to large-scale problem instances are presented. The paper also includes a review of the relevant literature

An evolutionary approach to a combined mixed integer programming model of seaside operations as arise in container ports

This paper puts forward an integrated optimisation model that combines three distinct problems, namely berth allocation, quay crane assignment, and quay crane scheduling that arise in container ports. Each one of these problems is difficult to solve in its own right. However, solving them individually leads almost surely to sub-optimal solutions. Hence, it is desirable to solve them in a combined form. The model is of the mixed-integer programming type with the objective being to minimize the tardiness of vessels and reduce the cost of berthing. Experimental results show that relatively small instances of the proposed model can be solved exactly using CPLEX. Large scale instances, however, can only be solved in reasonable times using heuristics. Here, an implementation of the genetic algorithm is considered. The effectiveness of this implementation is tested against CPLEX on small to medium size instances of the combined model. Larger size instances were also solved with the genetic algorithm, showing that this approach is capable of finding the optimal or near optimal solutions in realistic times

A comprehensive review of quay crane scheduling, yard operations and integrations thereof in container terminals

Over the past decades, container transportation has achieved considerable growth, and maritime trade now constitutes 80% of the global trade. The vessel sizes increased in parallel, up to 21,400 TEU (Twenty-foot-equivalent unit container). Accordingly, global containerized trade reached up to 150 million TEU in 2017 (UNCTAD 2018). This growth brings the need to use scientific methods to manage and operate container terminals more economically throughout the globe. In order to manage container transshipment and to use large vessels efficiently, the docking time at the container port for each vessel should be minimized. The decrease in the docking time enables the vessel to move to its next destination faster, decreasing turnover time and facilitating more containers to be transported. Container terminals can be divided into five main areas as the berth, the quay, the storage yard, the transport area, and the gate. The vessels must be berthed in suitable positions, after which many containers have to be unloaded or loaded via quay cranes, transshipped by vehicles inside the terminal, and stacked by yard cranes to suitable positions, all by using expensive equipment. With the invention of new technologies, the bottleneck at the berth side is almost overcome; however, the yard and the quayside operations have to be further perfected to obtain efficient plans. In this comprehensive literature review study, we aim to combine the literature on both yard and quayside operations, carefully examining independently studied problems as well as integrated ones. General information about port operations and relevant literature is provided. For the quayside, the literature on quay crane assignment and scheduling problems is investigated, whereas, for the yard side, yard crane scheduling, transport vehicle dispatching and scheduling, vehicle routing and traffic control, and storage location and space planning problems are reviewed in depth. In addition to these individual problems, their integrations are also analyzed, relevant publications and their respective contributions are explained in detail. Besides the milestone papers that lead the literature on container terminals, recent publications and advances are also reviewed, and managerial insights and future research directions are identified.Project Evaluation Commission of Yasar University [BAP038]The authors would like to thank the anonymous referees for their invaluable suggestions. This study was supported within the scope of the scientific research project, which was accepted by the Project Evaluation Commission of Yasar University under project number BAP038 and title Solution Approaches for Integrated Liner Shipping Network Design and Container Terminal Operations