Ruoxuan Xu

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About

Ruoxuan Xu is a researcher focused on intelligent logistics and industrial automation, with a particular emphasis on optimizing material handling systems in manufacturing environments. Their most notable contribution is the development of an improved genetic algorithm for multi-load Automated Guided Vehicle (AGV) scheduling, addressing critical inefficiencies in factories producing large parts. This work tackles the heavy workload and prolonged handling times associated with manual forklift operations, proposing a computational solution to enable intelligent, autonomous transportation within industrial settings. The research, published in 2023, has garnered 2 citations, signaling early recognition in the field of smart manufacturing and robotics. By integrating evolutionary algorithms with real-world logistical challenges, Xu's work contributes to the broader adoption of AGVs in automotive and heavy-part manufacturing, reducing human labor and increasing throughput. Their research bridges operations research and industrial engineering, offering practical pathways for factories transitioning to Industry 4.0 paradigms. Xu's focus on algorithm-driven automation positions them as an emerging voice in the optimization of cyber-physical production systems.