Order Picking

Order picking, the process of retrieving items from storage to fulfill orders, is a critical operation impacting warehouse efficiency and profitability. Current research focuses on optimizing picking routes and sequences using advanced algorithms like deep reinforcement learning, Markov decision processes, and multi-agent reinforcement learning, often considering dynamic order arrivals and human-robot collaboration. These efforts aim to minimize picking times, reduce operational costs, and improve customer experience, particularly in contexts like omnichannel retail and automated dispensing systems. The resulting improvements in efficiency and resource allocation have significant implications for logistics, supply chain management, and healthcare.