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.

翻译：优化仓库布局因其对效率和生产力具有显著影响而至关重要。本文提出了一种人工智能驱动的自动化仓库布局生成框架。该框架采用约束束搜索方法，在给定空间参数内推导出最优布局，并满足所有功能要求。生成布局的可行性基于物品可达性、所需最小净空以及通道连通性等标准进行验证。随后，使用评分函数对可行布局进行评估，考量因素包括存储位置数量、出入点数量以及可达性成本。我们证明了该方法能够为各种仓库尺寸与形状、多样化的门位置设置以及内部连接生成可行且最优的布局。这一目前正待部署的方法，将使人类设计者能够快速探索并确认多种方案，从而为其具体用例选择最合适的布局。