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In this paper, we review recent contributions dealing with the rehandling of containers at maritime container terminals. The problems studied in the paper refer to a post-stacking situation, i.e. problems arising after the stacking area has already been arranged. In order to increase efficiency of loading/unloading operations, once updated information about the state of the containers as well as of the vessels becomes available, it is possible to reshuffle the container yard, or a portion of it, in such a way that future loading operations are carried out with maximal efficiency. The increase in efficiency of loading/unloading operations has a bearing on the berthing time of the vessels, which, in turn, is a widely accepted indicator of port efficiency. Three types of post-stacking problems have been identified, namely (i) the remarshalling problem, (ii) the premarshalling problem, and (iii) the relocation problem. With respect to each of these problems, a thorough explanation of the problem itself, its relevance and its connections with other container handling issues are offered. In addition, algorithmic approaches to tackle such problems are summarized. IntroductionContainer terminals can be seen as buffers within larger logistic chains encompassing worldwide distribution systems. The major purpose of using container terminals is to serve as transshipment points. Container terminals are used as temporary storage points for containers, so that, e.g. unloading operations from a vessel and loading operations onto a train or a truck need not be synchronized.

Abstract. We discuss the blocks relocation problem (BRP), a specific problem in storing and handling of uniform blocks like containers. The BRP arises as an important subproblem of major logistic processes, like container handling on ships or bays, or storing of palettes in a stacking area. Any solution method for the BRP has to work with the stacking area and needs to draw relevant information from there. The strength of related approaches may rely on the extensive search of neighborhood structures. For an efficient implementation, fast access to data of the current stacking area and an efficient transformation into neighboring states is needed. For this purpose, we develop a binary description of the stacking area that fulfills the aforementioned requirements. We implement the binary representation and use it within a look ahead heuristic. Comparing our results with those from literature, our method outperforms best known approaches in terms of solution quality and computational time.

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