Joint configuration and scheduling optimization of the dual trolley quay crane and AGV for automated container terminal

Yue, Lijun; Fan, Houming; Zhai, Chunxin

doi:10.1088/1742-6596/1486/7/072080

Cited by 5 publications

(3 citation statements)

References 4 publications

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“…They designed a two-stage tabu search algorithm to minimize operational energy consumption. In a similar vein, Yue et al [10] designed an integrated scheduling model for dual-trolley QC and AGV, incorporating factors such as AGV endurance time. They utilized a genetic algorithm to minimize operational costs.…”

Section: Integrated Scheduling In Container Terminalmentioning

confidence: 99%

“…Equations ( 8) and ( 9) specify that every transportation task accomplished by the IGV is preceded and followed by other tasks. Equation (10) guarantees that each container is exclusively transported by a single IGV. Equation (11) states that if the IGV v handles container i, the task is either the first transportation task for the IGV v or the immediately following task for other containers.…”

Section: Constraints (1) Igv Operational Constraintsmentioning

confidence: 99%

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Energy-Aware Integrated Scheduling for Quay Crane and IGV in Automated Container Terminal

Luo,

Liang,

Zhang

et al. 2024

JMSE

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In this study, we address the integrated scheduling problem involving quay cranes and IGVs in automated terminals. We construct a mixed-integer planning model with the aim of minimizing the total energy consumption during quay crane and IGV operations, focusing on the loading-operation mode. The model considers the impact of the actual stowage of container ships on the loading order. We propose a dimension-by-dimension mutation sparrow search algorithm to optimize the model’s solution quality. Building upon the standard sparrow search algorithm, we incorporate cat mapping to enhance the diversity of the initial sparrow population. To improve global search in the early stage and local search in the later stage of the algorithm, we introduce an adaptive t-distribution mutation strategy. Finally, a total of 12 instances with container counts containing 30, 100, and 250 were designed for experiments to validate the effectiveness of the model and algorithm. The experiments demonstrate that, by appropriately increasing the number of quay cranes, configuring more than two or three IGVs can achieve optimal energy consumption for overall operations.

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Section: Integrated Scheduling In Container Terminalmentioning

confidence: 99%

Section: Constraints (1) Igv Operational Constraintsmentioning

confidence: 99%

Energy-Aware Integrated Scheduling for Quay Crane and IGV in Automated Container Terminal

Luo,

Liang,

Zhang

et al. 2024

JMSE

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“…Such a procedure also brought about the development of two hybrid evolutionary computation approaches that adopted genetic programming and genetic algorithm formulated for QCSPs with container groups that allow for easy location of near-optimal schedules with reasonable time for computations. Yue et al [19] proposed the two-phase scheduling optimization model to optimize the joint scheduling problem between dual-trolley quay crane and AGV.…”

Section: Related Workmentioning

confidence: 99%

A self-adaptation algorithm for quay crane scheduling at a container terminal

Yassen

Ayob

Jihad

et al. 2021

IJ-AI

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Quay cranes scheduling at container terminals is a fertile area of study that is attracting researchers as well as practitioners in different parts of the world, especially in OR and artificial intelligence (AI). This process efficiency may affect the accomplishment and the competitive merits. As such, four local search algorithms (LSs) are utilized in the current work. These are hill climbing (HC), simulated annealing (SA), tabu search (TS), and iterated local search (ILS). The results obtained demonstrated that none of these LSs succeeded to achieve good results on all instances. This is because different QCSP instances have different characteristics with NP-hardness nature. Therefore, it is difficult to define which LS can yield the best outcomes for all instances. Consequently, appropriate LS selection should be governed by the type of problem and search status. The current work proposes to achieve this, the self-adaptation heuristic (self-H). The self-H is composed of two separate stages: The upper (LS-controller) and the lower (QCSP-solver). The LS-controller embeds an adaptive selection mechanism to adaptively select which LS is to be adopted by the QCSP-solver to solve the given problem. The results revealed that the self-H outperformed others as it attained better results over most instances and competitive results.

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Survey of economic, energy and environmental aspects of cargo handling equipment in container ports

Lam

Chen

2021

2021 6th International Conference on Transportation Information and Safety (ICTIS)

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Joint configuration and scheduling optimization of the dual trolley quay crane and AGV for automated container terminal

Cited by 5 publications

References 4 publications

Energy-Aware Integrated Scheduling for Quay Crane and IGV in Automated Container Terminal

Energy-Aware Integrated Scheduling for Quay Crane and IGV in Automated Container Terminal

A self-adaptation algorithm for quay crane scheduling at a container terminal

Survey of economic, energy and environmental aspects of cargo handling equipment in container ports

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