Chinese Journal of Ship Research, Volume. 17, Issue 4, 155(2022)

Slotting optimization algorithm for automated 3D warehouse

Jianxin CHEN, Yuluo HUANG, Meng NING, and Guanfeng LI
Author Affiliations
  • Zhengzhou Institute of Electric and Mechanical Engineering, Zhengzhou 450015, China
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    Figures & Tables(13)
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    • Table 1. The action set of automated 3D warehouse

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      Table 1. The action set of automated 3D warehouse

      操作动作描述可执行动作
      储具左换层储具通过左通道移动至另一层某空储位任意两层左换层
      储具右换层储具通过右通道移动至另一层某空储位任意两层右换层
      储具入暂存区储具由当前位置换层入暂存区非暂存区库口储具入暂存区
      储具出暂存区储具由暂存区换层移出至某储位暂存区库口储具出至非暂存区
      储具顺时针循环某两行储具整体顺时针移动一位任意两行储具进行顺时针循环
      储具逆时针循环某两行储具整体逆时针移动一位任意两行储具进行逆时针循环
      储具左集合某行储具整体向左靠拢任意一行储具进行左集合移位
      储具右集合某行储具整体向右靠拢任意一行储具进行右集合移位
    • Table 2. Comparison on the slotting optimization steps of four algorithms

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      Table 2. Comparison on the slotting optimization steps of four algorithms

      储具规模运行步数
      基于贪心算法基于魔方还原算法普通MCTS算法SA-MCTS算法
      3×333314028
      3×437334534
      3×554406036
      3×663536343
      3×786626844
      3×8102707050
      3×9113758052
    • Table 3. Comparison on the storage optimization results of four algorithms

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      Table 3. Comparison on the storage optimization results of four algorithms

      算法库存均值库存方差
      3×73×83×93×73×83×9
      基于贪心算法2.6342.7222.7530.4080.4610.484
      基于魔方还原算法2.6032.5132.9250.47990.3220.468
      传统MCTS算法2.2382.8572.0950.4800.3290.480
      SA-MCTS算法2.9523.4282.8570.4730.2470.494
    • Table 4. Comparison on the slotting optimization results of four algorithms

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      Table 4. Comparison on the slotting optimization results of four algorithms

      算法时间复杂度解出比例/%平均计算时间/s优化耗时/h
      基于贪心算法$ O({n^2}) $850.9317.320
      基于魔方还原算法$ O({n^2}) $1000.8375.250
      传统MCTS算法$ O({n^3}) $751.2755.331
      SA-MCTS算法$ O({n^3}) $1001.1633.664
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    Jianxin CHEN, Yuluo HUANG, Meng NING, Guanfeng LI. Slotting optimization algorithm for automated 3D warehouse[J]. Chinese Journal of Ship Research, 2022, 17(4): 155

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    Paper Information

    Category: Ship Design and Performance

    Received: May. 7, 2021

    Accepted: --

    Published Online: Mar. 26, 2025

    The Author Email:

    DOI:10.19693/j.issn.1673-3185.02374

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