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AGV Scheduling Optimization of Automated Port Based on Disruption Management
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作者 Ching-Kuei Kao Qi-Er Ke +1 位作者 King-Zoo Tang Peng-Jung Lin 《Journal of Transportation Technologies》 2024年第3期423-444,共22页
The recent rapid development of China’s foreign trade has led to the significant increase in waterway transportation and automated container ports. Automated terminals can significantly improve the loading and unload... The recent rapid development of China’s foreign trade has led to the significant increase in waterway transportation and automated container ports. Automated terminals can significantly improve the loading and unloading efficiency of container terminals. These terminals can also increase the port’s transportation volume while ensuring the quality of cargo loading and unloading, which has become an inevitable trend in the future development of ports. However, the continuous growth of the port’s transportation volume has increased the horizontal transportation pressure on the automated terminal, and the problems of route conflicts and road locks faced by automated guided vehicles (AGV) have become increasingly prominent. Accordingly, this work takes Xiamen Yuanhai automated container terminal as an example. This work focuses on analyzing the interference problem of path conflict in its horizontal transportation AGV scheduling. Results show that path conflict, the most prominent interference factor, will cause AGV scheduling to be unable to execute the original plan. Consequently, the disruption management was used to establish a disturbance recovery model, and the Dijkstra algorithm for combining with time windows is adopted to plan a conflict-free path. Based on the comparison with the rescheduling method, the research obtains that the deviation of the transportation path and the deviation degree of the transportation path under the disruption management method are much lower than those of the rescheduling method. The transportation path deviation degree of the disruption management method is only 5.56%. Meanwhile, the deviation degree of the transportation path under the rescheduling method is 44.44%. 展开更多
关键词 automated Port Disruption Management automated guided vehicle scheduling Dijkstra Algorithm
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基于拥堵感知的自动化集装箱码头AGV充电策略
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作者 马宁丽 胡志华 《计算机集成制造系统》 EI CSCD 北大核心 2024年第7期2621-2630,共10页
为解决集装箱码头自动导引小车(AGV)作业过程中的拥堵、充电问题,以最小化AGV的完工时间为目标建立混合整数规划模型,提出分流拥堵路网分区中AGV的充电策略,并设计两阶段算法进行求解。第一阶段利用模拟退火算法优化AGV任务调度,第二阶... 为解决集装箱码头自动导引小车(AGV)作业过程中的拥堵、充电问题,以最小化AGV的完工时间为目标建立混合整数规划模型,提出分流拥堵路网分区中AGV的充电策略,并设计两阶段算法进行求解。第一阶段利用模拟退火算法优化AGV任务调度,第二阶段对于最优的AGV调度,进一步利用基于Dijkstra的拥堵预测算法应用拥堵感知充电策略优化AGV充电任务调度。实验表明拥堵感知充电策略比排队等待充电策略和按需充电策略分别平均节约了5.94%和2.73%的作业时间、方差分别为4.08和3.09。拥堵感知充电策略提高了AGV的作业效率,且其有效性与路段利用率、最大拥堵系数密切相关。 展开更多
关键词 自动化码头 自动导引车调度 充电策略 拥堵预测 模拟退火算法
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