Energy-aware Integrated Scheduling for Container Terminals with Conflict-free AGVs

Zhong, Zhaolin; Guo, Yong Feng; Zhang, Jihui; Yang, Shengxiang

doi:10.1007/s11518-023-5563-y

Cited by 9 publications

(3 citation statements)

References 46 publications

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“…Constraints ( 9) and (10) ensure that each AGV starts from the execution of a dummy starting task and ends with the execution of a dummy ending task. Constraint (11) is an arc balance constraint that ensures that the AGV should satisfy arc balance during the execution of loading, unloading, and battery-swapping tasks. Constraint (12) ensures that the start time of task i execution by AGV k is greater than or equal to the earliest time window of task i. Constraint (13) restricts the feasibility of the sequential processing time for AGV k to execute tasks i, j.…”

Section: The Mathematical Modelmentioning

confidence: 99%

“…They established an integrated scheduling model of the QCs, AGVs, and double-cantilever rail cranes to minimize the processing time and a conflict-free path planning model to minimize the transportation time of the AGVs. Zhong et al [11] constructed a mixed-integer programming model to optimize the joint scheduling of AGVs and YCs, minimizing the total energy consumption for given loading and unloading tasks. They considered conflict-free path planning for AGVs and the capacity constraints of the AGV mate, and designed a novel bi-level genetic algorithm for solving this model.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Automatic Guided Vehicle Scheduling in Automated Container Terminals Based on a Hybrid Mode of Battery Swapping and Charging

Xiao,

Huang,

et al. 2024

JMSE

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Automatic guided vehicles (AGVs) in the horizontal area play a crucial role in determining the operational efficiency of automated container terminals (ACTs). To improve the operational efficiency of an ACT, it is essential to decrease the impact of battery capacity limitations on AGV scheduling. To address this problem, this paper introduces battery swapping and opportunity charging modes into the AGV system and proposes a new AGV scheduling problem considering the hybrid mode. Firstly, this study describes the AGV scheduling problem of the automated container terminals considering both loading and unloading tasks under the hybrid mode of battery swapping and charging. Thereafter, a mixed-integer programming model is established to minimize the sum of energy costs and delay costs. Secondly, an effective adaptive large neighborhood search algorithm is proposed to solve the problem, in which the initial solution construction, destroy operators, and repair operators are designed according to the hybrid mode. Finally, numerical experiments are conducted to analyze the effectiveness of the model and the optimization performance of the algorithm. The results demonstrate that the hybrid mode of battery swapping and charging can effectively reduce the number of battery swapping times and scheduling costs compared to the existing mode.

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Section: The Mathematical Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Automatic Guided Vehicle Scheduling in Automated Container Terminals Based on a Hybrid Mode of Battery Swapping and Charging

Xiao,

Huang,

et al. 2024

JMSE

View full text Add to dashboard Cite

show abstract

“…This improved the search accuracy of the genetic algorithm and optimized energy consumption. Zhong et al [31] devised a two-layer genetic algorithm for the integrated scheduling problem of QC, AGV, and YC, searching for the optimal scheduling scheme of QC and YC. They proposed a conflict-free path-solving strategy, enabling AGVs to achieve minimal operation energy consumption without the loss of utilization.…”

Section: Energy Saving and Emission Reduction In Container Terminalmentioning

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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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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Systems thinking and time-independent solutions for integrated scheduling in automated container terminals

Zhang,

Zhuang,

Qin

et al. 2024

Advanced Engineering Informatics

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Energy-aware Integrated Scheduling for Container Terminals with Conflict-free AGVs

Cited by 9 publications

References 46 publications

Automatic Guided Vehicle Scheduling in Automated Container Terminals Based on a Hybrid Mode of Battery Swapping and Charging

Automatic Guided Vehicle Scheduling in Automated Container Terminals Based on a Hybrid Mode of Battery Swapping and Charging

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

Systems thinking and time-independent solutions for integrated scheduling in automated container terminals

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