An Attention Model Based Heuristic Algorithm for Storage Selection and Order Picking Path Joint Optimization

This research introduces an advanced attention-driven model designed to optimize warehouse order-picking, an enhancement of the foundational work by Kool et al. (2018). Fundamentally, our model incorporates an enhanced masking mechanism and context-aware decoder, streamlining the orderpicking process. In essence, our model presents an attention model based heuristic solution to the long-standing problem of orderpicking optimization, leveraging the latest in attention-based deep learning and reinforcement learning techniques. Compared to existing methods, our innovative model shows superior performance, offering significant potential in warehousing solutions.