Research into container reshuffling and stacking problems in container terminal yards

Container stacking and reshuffling are important issues in the management of operations in a container terminal. Minimizing the number of reshuffles can increase productivity of the yard cranes and the efficiency of the terminal. In this research, the authors improve the existing static reshuffling model, develop five effective heuristics, and analyze the performance of these algorithms. A discrete-event simulation model is developed to animate the stacking, retrieving, and reshuffling operations and to test the performance of the proposed heuristics and their extended versions in a dynamic environment with arrivals and retrievals of containers. The experimental results for the static problem show that the improved model can solve the reshuffling problem more quickly than the existing model and the proposed extended heuristics are superior to the existing ones. The experimental results for the dynamic problem show that the results of the extended versions of the five proposed heuristics are superior or similar to the best results of the existing heuristics and consume very little time

Sea Container Terminals

Due to a rapid growth in world trade and a huge increase in containerized goods, sea container terminals play a vital role in globe-spanning supply chains. Container terminals should be able to handle large ships, with large call sizes within the shortest time possible, and at competitive rates. In response, terminal operators, shipping liners, and port authorities are investing in new technologies to improve container handling infrastructure and operational efficiency. Container terminals face challenging research problems which have received much attention from the academic community. The focus of this paper is to highlight the recent developments in the container terminals, which can be categorized into three areas: (1) innovative container terminal technologies, (2) new OR directions and models for existing research areas, and (3) emerging areas in container terminal research. By choosing this focus, we complement existing reviews on container terminal operations

Optimization of Container Terminal Operations

Over the last years, international sea-freight container transportation has grown dramatically and container terminals play nowadays a key-role in the global shipping network. The increased competitiveness among terminals requires more and more efficiency in container operations, both along the quayside and within the yard, in order to minimize ships turnaround time. Operations research methods and techniques are therefore worth being used in optimizing terminal operations. In this work, we first give an overview of decision problems which arise in the management of a container terminal (e.g. berth allocation, crane scheduling, storage policies and strategies, transfer operations) and we briefly describe models and methods presented in the literature. Then, starting from a collaboration with some of the busiest ports in Europe, we have identified some critical issues which will be illustrated: in particular, we focus on the impact that gate operations and transshipment operations have on the yard and we propose a new approach to the yard management which takes into account these interactions. We conclude with suggestions of possible research tracks and open issues

Reshuffle minimisation to improve storage yard operations efficiency

There are many ways to measure the efficiency of the storage area management in container terminals. These include minimising the need for container reshuffle especially at the yard level. In this paper, we consider the container reshuffle problem for stacking and retrieving containers. The problem was represented as a binary integer programming model and solved exactly. However, the exact method was not able to return results for large instances. We therefore considered a heuristic approach. A number of heuristics were implemented and compared on static and dynamic reshuffle problems including four new heuristics introduced here. Since heuristics are known to be instance dependent, we proposed a compatibility test to evaluate how well they work when combined to solve a reshuffle problem. Computational results of our methods on realistic instances are reported to be competitive and satisfactory

Intelligent planning for allocating containers in maritime terminals

Maritime container terminals are facilities where cargo containers are transshipped between ships or between ships and land vehicles (tucks or trains). These terminals involve a large number of complex and combinatorial problems. One of them is related to the Container Stacking Problem. A container yard is a type of temporary store where containers await further transport by truck, train or vessel. The main efficiency problem for an individual stack is to ensure easy access to containers at the expected time of transfer. Stacks are 'last-in, first-out' storage structures where containers are stocked in the order they arrive. But they should be retrieved from the stack in the order (usually different) they should be shipped. This retrieval operation should be efficiently performed, since berthing time of vessels and the terminal operations should be optimized. To do this, cranes can relocate containers in the stacks to minimize the rearrangements required to meet the expected order of demand for containers. In this paper, we present a domain-dependent heuristically guided planner for obtaining the optimized reshuffling plan, given a stacking state and a container demand. The planner can also be used for finding the best allocation of containers in a yard-bay in order to minimize the number of reshuffles as well as to be used for simulation tasks and obtaining conclusions about possible yard configurations. © 2011 Elsevier Ltd. All rights reserved.This work has been partially supported by the research projects TIN2010-20976-C02-01 (Min. de Ciencia e Innovacion, Spain), P19/08 (Min. de Fomento, Spain-FEDER) and the VALi+d Program of the Conselleria d'Educacio (Generalitat Valenciana), as well as with the collaboration of the maritime container terminal MSC (Mediterranean Shipping Company S.A.).Rodríguez Molins, M.; Salido Gregorio, MA.; Barber Sanchís, F. (2012). Intelligent planning for allocating containers in maritime terminals. Expert Systems with Applications. 39(1):978-989. https://doi.org/10.1016/j.eswa.2011.07.098S97898939

Modelling of integrated vehicle scheduling and container storage problems in unloading process at an automated container terminal

Effectively scheduling vehicles and allocating storage locations for containers are two important problems in container terminal operations. Early research efforts, however, are devoted to study them separately. This paper investigates the integration of the two problems focusing on the unloading process in an automated container terminal, where all or part of the equipment are built in automation. We formulate the integrated problem as a mixed-integer programming (MIP) model to minimise ship’s berth time. We determine the detailed schedules for all vehicles to be used during the unloading process and the storage location to be assigned for all containers. A series of experiments are carried out for small-sized problems by using commercial software. A genetic algorithm (GA) is designed for solving large-sized problems. The solutions from the GA for the small-sized problems are compared with the optimal solutions obtained from the commercial software to verify the effectiveness of the GA. The computational results show that the model and solution methods proposed in this paper are efficient in solving the integrated unloading problem for the automated container terminal

Optimizing the Landside Operation of a Container Terminal

This paper concerns the problem of operating a landside container exchange area that is serviced by multiple semi-automated rail mounted gantry cranes (RMGs) that are moving on a single bi-directional traveling lane. Such a facility is built by Patrick Corporation at the Port Botany terminal in Sydney. The gantry cranes are a scarce resource and handle the bulk of container movements. Thus, they require a sophisticated analysis to achieve near optimal utilization. We present a three stage algorithm to manage the container exchange facility, including the scheduling of cranes, the control of associated short-term container stacking, and the allocation of delivery locations for trucks and other container transporters. The key components of our approach are a time scale decomposition, whereby an integer program controls decisions across a long time horizon to produce a balanced plan that is fed to a series of short time scale online subproblems, and a highly efficient space-time divisioning of short term storage areas