Bi-Objective Integrated Scheduling of Quay Cranes and Automated Guided Vehicles

Duan, Yao; Ren, Hongxiang; Xu, Fengming; Yang, Xin‐She; Meng, Yao

doi:10.3390/jmse11081492

Cited by 8 publications

(7 citation statements)

References 42 publications

(62 reference statements)

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“…Nevertheless, they weighted the two objectives when implementing the solution method, posing challenges to ensuring the reasonable allocation of objective weights. Duan et al [13] established a multiobjective integrated scheduling model targeting overall makespan and AGV unloading time. They employed NSGA-II to obtain a noninferior solution set, demonstrating superior results compared to the weighted method under a large number of tasks.…”

Section: Integrated Scheduling 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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Section: Integrated Scheduling 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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“…Wang et al (2022) investigated the AGV scheduling problem considering bidirectional paths in ACTs and designed a branch-and-bound algorithm to generate conflict-free routes and minimize the total completion time [4]. Duan et al (2023) studied the AGV scheduling problem considering the interaction with QC, and a mixed integrated programming model was established with the goal of minimizing the completion time of ships and the idle time of AGVs [5]. studied the AGV scheduling problem under the sea rail intermodal transportation model and established a mixed integer programming model to minimize equipment energy consumption [8].…”

Section: Literature Reviewmentioning

confidence: 99%

“…Unlike the conventional AGV scheduling [1][2][3][4][5], when studying the AGV scheduling problem in a new type of automated container terminal, it is necessary to pay attention to its battery consumption, ensuring that the depleted AGVs can be restored in a timely manner while completing their task, thereby ensuring the smooth completion of container transportation. At the same time, it is necessary to consider the charging capacity of the terminal to avoid congestion of AGVs with depleted batteries at the battery-swapping station and consider factors that affect the energy consumption of AGVs, such as their driving speed, often influenced by the traffic environment in different areas of the terminal.…”

Section: Introductionmentioning

confidence: 99%

Automated Guided Vehicle (AGV) Scheduling in Automated Container Terminals (ACTs) Focusing on Battery Swapping and Speed Control

Yang,

Hu,

Cheng

et al. 2023

JMSE

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Because they are environmentally friendly and safe, automated guided vehicles (AGVs) are increasingly used in newly constructed automated container terminals. However, their scheduling strategy is constrained by their limited battery capacity. When batteries reach their charging threshold, the AGVs need to be returned to battery-swapping stations. Moreover, the movement speed of AGVs has a significant impact on their energy consumption and operating times. Therefore, in this paper, a speed control strategy that considers the traffic environment of the terminal is proposed from the perspective of energy conservation and emission reduction. In addition, the charging capacity of the terminal is discretized to model its limited handling capacity to avoid congestion in the battery-swapping stations. To minimize the costs of delays and carbon emissions of AGV operations, a mixed integer programming model is established. It optimizes the efficiency and carbon emissions of the operations by assigning and prioritizing container transportation and AGV battery-swapping tasks. An improved genetic algorithm-based approach is designed where a better initial solution is obtained through a greedy strategy, while simulated annealing is adopted for population selection to prevent the algorithm from falling into local optima. Furthermore, an adaptive adjustment strategy for crossover and mutation probabilities is adopted to improve the algorithm’s convergence. Finally, a series of numerical experiments is conducted to verify the efficiency of the proposed method. The experimental results indicate that considering the variability of AGV speed can more accurately characterize their energy consumption, and increasing the number of AGVs and enhancing the battery-swapping capacity can effectively reduce the costs of delays and carbon emissions.

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“…Yue et al [13] established a two-phase mathematical model for dual-trolley QCs and AGVs by considering constraints such as vessel stability and aiming at the total energy consumption during loading and discharging operations. Duan et al [14] developed a two-phase mathematical model for the integrated scheduling problem for the QCs and AGVs to minimize the makespan and the unloaded time of AGVs. The related research results are valuable for the improvement of the overall operation efficiency and energy consumption optimization of terminals, but there is still a lack of specific depictions of the operation flow of AGV subsystems and related constraints.…”

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

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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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Bi-Objective Integrated Scheduling of Quay Cranes and Automated Guided Vehicles

Cited by 8 publications

References 42 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

Automated Guided Vehicle (AGV) Scheduling in Automated Container Terminals (ACTs) Focusing on Battery Swapping and Speed Control

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

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