A decomposition method for finding optimal container stowage plans

In transportation of goods in large container ships, shipping industries need to minimize the time spent at ports to load/unload containers. An optimal stowage of containers on board minimizes unnecessary unloading/reloading movements, while satisfying many operational constraints. We address the basic container stowage planning problem (CSPP). Different heuristics and formulations have been proposed for the CSPP, but finding an optimal stowage plan remains an open problem even for small-sized instances. We introduce a novel formulation that decomposes CSPPs into two sets of decision variables: the first defining how single container stacks evolve over time and the second modeling port-dependent constraints. Its linear relaxation is solved through stabilized column generation and with different heuristic and exact pricing algorithms. The lower bound achieved is then used to find an optimal stowage plan by solving a mixed-integer programming model. The proposed solution method outperforms the methods from the literature and can solve to optimality instances with up to 10 ports and 5,000 containers in a few minutes of computing time

Including containers with dangerous goods in the Slot Planning Problem

Container stowage problems are rich optimization problems with both high economic and environmental impact. These problems are typically decomposed into a master bay planning phase, which distributes containers to bay sections of the vessel, and a slot planning phase, which assigns a specific slot within the bay section to each container. In this paper, we extend existing models for slot planning by considering containers with dangerous goods. An important contribution of this paper is that we provide a model closer to the real-world problems faced by planners, and thus solutions based on this model should be easier to implement in practice. We show that our model can be solved to optimality in reasonable time using standard software like Gurobi or CPLEX. Keywords: operations research, container stowage, optimization, logisticspublishedVersio

Solving the generalized multi-port container stowage planning problem by a matheuristic algorithm

We focus on a simplified container stowage planning problem where containers of different size and weight must be loaded and unloaded at multiple ports while maintaining the stability of the ship. We initially investigate how the difficulty in solving the problem changes with and without the consideration of container sizes and weight constraints. For this purpose, we provide integer programming formulations for the general problem as well as some special cases with identical container size and/or identical weights and evaluate their performance in randomly generated small- and medium-scale instances. We develop a matheuristic procedure, namely, an insert-and-fix heuristic, exploiting the special structure of the proposed formulations. The Insert-and-Fix method, in combination with a constructive algorithm that gives the solver an initial solution in each iteration, provides solutions with a low number of rehandles for instances with up to 5000 TEUs.Spanish Ministry of Science, Innovation, and Universities, FPU Grant A-2015-12849 and under the project “OPTEP-Port Terminal Operations Optimization” (No. RTI2018-094940-B-I00) financed with FEDER, Spain funds. The second author acknowledges the partial support by Data-driven logistics, Spain (FWO-S007318N) and Internal Funds KU Leuven, Spain

Containership Load Planning with Crane Operations

Since the start of the containerization revolution in 1950's, not only the TEU capacity of the vessels has been increasing constantly, but also the number of fully cellular container ships has expanded substantially. Because of the tense competition among ports in recent years, improving the operational efficiency of ports has become an important issue in containership operations. Arrangement of containers both within the container terminal and on the containership play an important role in determining the berthing time. The berthing time of a containership is mainly composed of the unloading and loading time of containers. Containers in a containership are stored in stacks, making a container directly accessible only if it is on the top of one stack. The task of determining a good container arrangement to minimize the number of re-handlings while maintaining the ship's stability over several ports is called stowage planning, which is an everyday problem solved by ship planners. The horizontal distribution of the containers over the bays affects crane utilization and overall ship berthing time. In order to increase the terminal productivity and reduce the turnaround time, the stowage planning must conform to the berth design. Given the configuration of berths and cranes at each visiting port, the stowage planning must take into account the utilization of quay cranes as well as the reduction of unnecessary shifts to minimize the total time at all ports over the voyage. This dissertation introduces an optimization model to solve the stowage planning problem with crane utilization considerations. The optimization model covers a wide range of operational and structural constraints for containership load planning. In order to solve real-size problems, a meta-heuristic approach based on genetic algorithms is designed and implemented which embeds a crane split approximation routine. The genetic encoding is ultra-compact and represents grouping, sorting and assignment strategies that might be applied to form the stowage pattern. The evaluation procedure accounts for technical specification of the cranes as well as the crane split. Numerical results show that timely solution for ultra large size containerships can be obtained under different scenarios

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