Qinqi Chen

Papers

Total Citations

H-Index

About

Qinqi Chen is a researcher in manufacturing automation and robotic systems, with a particular focus on optimizing welding processes through intelligent computational methods. Their most cited work, "Hybrid genetic-ant colony algorithm based job scheduling method research of arc welding robot," addresses the challenge of efficient job scheduling for arc welding robots by modeling the problem as a Traveling Salesman Problem (TSP). Chen’s key contribution lies in designing a hybrid optimization approach that combines genetic algorithms and ant colony optimization to minimize welding path lengths and improve production efficiency. This work, with 6 citations, has provided a foundational framework for integrating bio-inspired algorithms into industrial robotics scheduling. Chen’s research bridges the gap between theoretical algorithm design and practical manufacturing applications, offering solutions that reduce operational costs and enhance robot utilization. By tackling the combinatorial complexity of welding job sequencing, Chen has contributed to the broader field of intelligent manufacturing, where adaptive, nature-inspired algorithms are increasingly used to solve real-world production challenges. Their work remains relevant for researchers exploring hybrid metaheuristics in robotics and automated manufacturing systems.