Max Robotics — Global Service Robot Directory + US Certification

About

Lining Xing is a leading researcher in intelligent manufacturing and swarm robotics, with a focus on optimizing production logistics through advanced computational methods. Their work addresses critical challenges in smart manufacturing systems, particularly the scheduling and coordination of mobile robots for efficient material handling. Xing’s most cited paper, "Multi-mobile robots and multi-trips feeding scheduling problem in smart manufacturing system: An improved hybrid genetic algorithm" (2019, 7 citations), introduces a novel hybrid genetic algorithm that significantly enhances the timeliness and reliability of supply chains in modern factories. They further advanced the field with a multi-objective optimization method for swarm robotic control models (2020, 5 citations), enabling robots to adapt to changing parameters and conditions—a key step toward self-organized, flexible automation. Their research on scheduling mobile robots in flexible manufacturing systems using adaptive large neighborhood search (2020, 2 citations) demonstrates practical solutions for path planning and goods transport. Xing’s contributions are pivotal for industries seeking to integrate robotics into production, reducing errors and boosting efficiency. Their work not only pushes the boundaries of algorithmic optimization but also provides tangible frameworks for real-world smart factory implementations, making Xing a key figure in the evolution of intelligent manufacturing and autonomous robotic systems.