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基于强化学习的无人车组路径优化算法研究
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作者 司炳山 董志明 孙茂凡 《计算机仿真》 2024年第2期455-461,共7页
针对传统单车路径规划算法在进行无人车组路径规划时存在的算法收敛性问题,采用强化学习方法,对传统Q-learning算法中的探索率进行改进,将每一个路程点作为每一段局部路径规划的目标点,通过传感器感知外界环境的信息,进行基于强化学习... 针对传统单车路径规划算法在进行无人车组路径规划时存在的算法收敛性问题,采用强化学习方法,对传统Q-learning算法中的探索率进行改进,将每一个路程点作为每一段局部路径规划的目标点,通过传感器感知外界环境的信息,进行基于强化学习的在线局部路径规划,完成避障和寻径任务。构建了算法模型与仿真环境,并进行了仿真,结果表明无人车组能够在短时间内收敛到稳定状态并自主完成规划任务,证明了算法的有效性和可行性。上述算法在多无人战车协同的智能规划与控制中具有良好的应用前景。 展开更多
关键词 强化学习 无人战车 路径优化 探索率
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The RHSA Strategy for the Allocation of Outbound Containers Based on the Hybrid Genetic Algorithm 被引量:1
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作者 Meilong Le Hang Yu 《Journal of Marine Science and Application》 2013年第3期344-350,共7页
Secure storage yard is one of the optimal core goals of container transportation;thus,making the necessary storage arrangements has become the most crucial part of the container terminal management systems(CTMS).Thi... Secure storage yard is one of the optimal core goals of container transportation;thus,making the necessary storage arrangements has become the most crucial part of the container terminal management systems(CTMS).This paper investigates a random hybrid stacking algorithm(RHSA) for outbound containers that randomly enter the yard.In the first stage of RHSA,the distribution among blocks was analyzed with respect to the utilization ratio.In the second stage,the optimization of bay configuration was carried out by using the hybrid genetic algorithm.Moreover,an experiment was performed to test the RHSA.The results show that the explored algorithm is useful to increase the efficiency. 展开更多
关键词 random hybrid stacking algorithm genetic algorithm container yard operation container stowage plan handling cost utilization ratio
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