Jialei Liu

Papers

Total Citations

H-Index

About

Jialei Liu’s research centers on the intersection of artificial intelligence, robotics, and warehouse automation, with a particular focus on optimizing Automated Retrieval Systems (ARS) in smart warehouses. Their most-cited work, "Efficient Order-based Scheduling Algorithms for Automated Retrieval System (ARS) in Smart Warehouses" (2020), introduces novel scheduling algorithms that integrate AI-driven decision-making to streamline product retrieval processes, reducing operational delays and improving throughput in automated logistics environments. This contribution addresses a critical bottleneck in modern supply chains, where the demand for rapid, accurate order fulfillment is paramount. By designing algorithms that prioritize order-based sequencing, Liu’s work enhances the coordination between robotic systems and warehouse management software, offering scalable solutions for industries transitioning to smart warehousing. With 2 citations, this paper has laid foundational groundwork for further studies in robotic scheduling and warehouse optimization. Liu’s research is particularly notable for its practical applications, bridging theoretical algorithm design with real-world industrial challenges. Their achievements highlight a commitment to advancing automation technologies that drive efficiency in e-commerce and logistics sectors, making their work essential reading for researchers and engineers seeking to improve the intelligence of warehouse operations.