杨玮,张子涵,张晓楠,马伟.新型无人仓AutoStore的货物合箱方法研究[J].包装工程,2022,43(17):174-183.
YANG Wei,ZHANG Zi-han,ZHANG Xiao-nan,MA Wei.Cargo Consolidation Method in New Unmanned Warehouse AutoStore[J].Packaging Engineering,2022,43(17):174-183. |
| 新型无人仓AutoStore的货物合箱方法研究 |
| Cargo Consolidation Method in New Unmanned Warehouse AutoStore |
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| DOI：10.19554/j.cnki.1001-3563.2022.17.022 |
| 中文关键词: AutoStore系统 存储策略 Apriori关联规则挖掘算法 混沌种子优化算法 |
| 英文关键词: AutoStore system storage strategy Apriori association rule mining algorithm chaotic seed optimization algorithm |
| 基金项目:国家自然科学基金青年科学基金(71802120);西安市未央区项目(201939) |
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| 中文摘要: |
| 目的 为减少AutoStore系统在共同存储策略下的订单处理时间，解决经营品类繁多，但仓储面积有限的企业货物存储问题。方法 提出货物合箱的存储方法，设计关联规则挖掘算法与混沌种子优化算法的混合优化算法进行求解。从机器人翻箱操作、料箱的分配规则、系统布局三方面进行分析，结合AutoStore运作规律，建立以机器人拣货行走距离最短为目标函数的数学模型，通过Apriori算法输出货物热度，输入混沌种子算法，得到储位分配结果，实现联动决策。在基本种子算法的迭代中加入混沌序列，帮助种子避开局部极小值。结果 实例分析表明，货物合箱方法能够显著减少共同存储下AutoStore系统的订单处理时间，缩小与指定存储策略订单处理时间的差距，与粒子群算法和基本种子优化算法相比，混沌种子优化算法的优化效率更高、稳定性更好。结论 文中的研究为经营品类繁多，但仓储面积有限的企业提供了一种更适合的货物存储策略，具有较强的操作性和实际意义。 |
| 英文摘要: |
| The work aims to reduce the order processing time of the AutoStore system under the common storage strategy and solve the storage problem encountered by companies with a wide range of goods but limited storage area. A storage method of cargo consolidation was proposed, and a hybrid optimization algorithm of association rule mining algorithm and chaotic seed optimization algorithm was designed for solution. Then, the analysis was carried out from the three aspects of robot turning operation, bin distribution rules, and system layout. Combined with AutoStore operation rules, a mathematical model with the shortest walking distance of robot picking as the objective function was established to output the heat of the goods through the Apriori algorithm, and input the chaotic seed algorithm to get the storage allocation result, thus realizing the linkage decision-making. The chaotic sequence was added in the iteration of the basic seed algorithm to help the seed avoid local minima. The case analysis showed that the cargo consolidation method could significantly reduce the order processing time of the AutoStore system under common storage, and narrow the gap with the specified storage strategy order processing time. Compared with the particle swarm optimization algorithm and the basic seed optimization algorithm, the chaotic seed optimization algorithm had higher optimization efficiency and better stability. This research provides a more suitable cargo storage strategy for companies with a wide range of business categories but limited storage area, which has strong operability and practical significance. |
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