Research into container reshuffling and stacking problems in container terminal yards

Tang, Lixin; Wei, Junhu; Liu, Jiyin; Dong, Yuxiao

doi:10.1080/0740817x.2014.971201

Cited by 50 publications

(17 citation statements)

References 19 publications

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“…After this exhaustive review, we believe that the heuristics we introduce here has the following advantages in particular over those described in Tang et al 28 1. Four new simple but still effective heuristics are introduced.…”

Section: Literature Reviewmentioning

confidence: 93%

Reshuffle minimisation to improve storage yard operations efficiency

Bisira

Salhi

2021

Journal of Algorithms & Computational Technology

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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.

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Section: Literature Reviewmentioning

confidence: 93%

Reshuffle minimisation to improve storage yard operations efficiency

Bisira

Salhi

2021

Journal of Algorithms & Computational Technology

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“…Besides, Wan, Liu, and Tsai (2009), Yang and Kim (2006), Hakan Akyüz and Lee (2014), and Tang, Jiang, Liu, and Dong (2014) extend the general CRP by minimizing the number of reshuffles when assigning storage locations for incoming and reshuffled export containers, defined as the dynamic container relocation problem (DCRP). Lee and Lee (2010) extend the BRP to multiple bays by minimizing the number of container movements and the crane's operating time.…”

Section: Introductionmentioning

confidence: 99%

Mathematical formulation and heuristic algorithm for the block relocation and loading problem

Zhu

Guo

et al. 2019

Naval Research Logistics

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This study considers the block relocation and loading problem in container terminals. The optimal loading sequence and relocation location are simultaneously decided on the basis of the desired ship‐bay and initial yard space configuration. An integer linear programming model is developed to minimize the number of relocations in the yard space on the basis of no shifts in the ship bay. The accuracy of the model is tested on small‐scale scenarios by using CPLEX. Considering the problem size in the real world, we present a rule‐based heuristic method that is combined with a mathematical model for the removal, loading, and relocation operations. The influence of rules on algorithm performance is also analyzed, and the heuristic algorithm is compared with different types of algorithms in the literature. The extensive numerical experiments show the efficiency of the proposed heuristic algorithm.

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“…Caserta et al (2012) propose another intuitive formulation of the problem, called BRP-II, as well as an efficient heuristic. Tang et al (2015) propose a very similar formulation with fewer variables than in BRP-II, present heuristics and a worst case analysis. Expósito-Izquierdo et al (2015) correct BRP-II and rename their new formulation BRP-II*.…”

Section: Introductionmentioning

confidence: 99%