自动生成仓库布局的新型框架。

IF 3 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Frontiers in Artificial Intelligence Pub Date : 2024-10-15 eCollection Date: 2024-01-01 DOI:10.3389/frai.2024.1465186
Atefeh Shahroudnejad, Payam Mousavi, Oleksii Perepelytsia, Sahir, David Staszak, Matthew E Taylor, Brent Bawel
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引用次数: 0

摘要

优化仓库布局对效率和生产率有重大影响,因此至关重要。我们提出了一种人工智能驱动的自动仓库布局生成框架。该框架采用约束波束搜索,在给定的空间参数内生成最优布局,同时满足所有功能要求。生成布局的可行性根据物品可及性、所需最小间隙和通道连通性等标准进行验证。然后,考虑到存储位置、存取点和存取成本的数量,使用评分函数对可行布局进行评估。我们展示了我们的方法能够为各种仓库尺寸和形状、不同的门位置和相互连接产生可行的最佳布局。这种方法目前正准备投入使用,它将使人类设计师能够快速探索和确认各种选项,从而为他们选择最合适的布局方案提供便利。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A novel framework for automated warehouse layout generation.

Optimizing warehouse layouts is crucial due to its significant impact on efficiency and productivity. We present an AI-driven framework for automated warehouse layout generation. This framework employs constrained beam search to derive optimal layouts within given spatial parameters, adhering to all functional requirements. The feasibility of the generated layouts is verified based on criteria such as item accessibility, required minimum clearances, and aisle connectivity. A scoring function is then used to evaluate the feasible layouts considering the number of storage locations, access points, and accessibility costs. We demonstrate our method's ability to produce feasible, optimal layouts for a variety of warehouse dimensions and shapes, diverse door placements, and interconnections. This approach, currently being prepared for deployment, will enable human designers to rapidly explore and confirm options, facilitating the selection of the most appropriate layout for their use-case.

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来源期刊
CiteScore
6.10
自引率
2.50%
发文量
272
审稿时长
13 weeks
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