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Optimization of Sorting Activities in Automatic Storage and Retrieval Systems Based on Improved Artificial Fish Swarm Algorithm

机译:基于改进人工鱼群算法的自动仓储系统分拣活动优化

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For the problem of picking path planning in automatic storage, the traditional artificial fish swarm algorithm is improved to be used to optimize the picking system. In the algorithm, the calculation of dynamic parameters is added, so that the field of view and step size of the algorithm are dynamically changed to adapt to the convergence process of the algorithm; the chaotic model is added for initialization to obtain a better initial individual distribution. Experiments show the improved algorithm is feasible in the sorting activities in automatic storage and retrieval systems.
机译:针对自动仓库中的拣选路径规划问题,对传统的人工鱼群算法进行了改进,以优化拣选系统。该算法增加了动态参数的计算,可以动态改变算法的视场和步长,以适应算法的收敛过程。添加混沌模型以进行初始化以获得更好的初始个体分布。实验表明,改进的算法在自动存储和检索系统中的分类活动中是可行的。

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