  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.
