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TopThe authors now review the different methods of containers stored in a containership, which have been considered in the past, to situate the present work.
In (Avriel & Penn,1993; Avriel, Penn, Shpirer, & Witteboon, 1998), a mathematical model for stowage planning for a containership is presented without considering the stability of the vessel. The goal is to minimize the number of displacements.
In view of (Wilson & Roach, 2000), determining an optimal solution to the problem of loading and unloading containers seems difficult and even impracticable within a reasonable time. This is a complex problem, depending on the capacity of the vessel and the number of containers unloaded and loaded at each port. Therefore, the authors of this paper propose to break the process into two sub-processes, a strategic process, and a tactical planning process. In the first step, a Branch and Bound algorithm is used to allocate every container to a ship block. The Taboo search is then used to assign containers to specific locations within the blocks determined in the first phase. Thus, acceptable but not always optimal solutions can be determined in real-time within a reasonable calculation time.
The work (Imai, Nishimura, Papadimitriou, & Sasaki, 2002) is one of the first models of stowage planning that considers the minimization of storage operations. The model formulates the stability of the boat only in terms of the distance between the center of gravity and the metacenter. No distinction is made between the different types of containers or between their destinations. An estimate of the number of maneuvers is calculated, which are also included in the objective function.
In (Imai, Sasaki, Nishimura, & Papadimitriou, 2006), the authors include two new constraints for the calculation of stability (longitudinal and transverse stability of the vessel) compared to their previous model. The problem is formulated as a multi-objective program in whole numbers. Because of the complexity of the model, the authors propose a solution approach based on genetic algorithms.
The work presented in (Sciomachen & Tanfani, 2007) develops a heuristic algorithm to solve this same problem. The goal of the authors is to reduce the total loading time. A confirmation of the proposed approach with a few test cases concerning containership quays in the port of Genoa (Italy) is given.
(Monaco, Sammarra, & Sorrentino, 2014) are involved in the problem of determining the optimal position of containers to be stored in a ship. They assume that the ship’s berthing along the quay is composed of several slots. They propose a binary integer program and a two-step heuristic algorithm to find effective solutions to the problem of storage planning.