Qiyao Duan
Papers
1
Total Citations
4
H-Index
1
About
Qiyao Duan is a rising researcher in sustainable manufacturing and intelligent optimization, whose work focuses on advancing human-robot collaboration in remanufacturing systems. Their key research areas include disassembly line balancing, evolutionary algorithms, and human-robot shared-workstation design. Duan's most notable contribution is the development of a genetic teaching-learning-based optimisation algorithm, which significantly enhances remanufacturing efficiency by optimizing task allocation between human workers and robots in complex disassembly environments. This work, published in 2025, has already garnered 4 citations, reflecting its timely relevance to Industry 4.0 and circular economy goals. By addressing the critical challenge of balancing productivity with flexibility in remanufacturing, Duan's research offers practical solutions for reducing waste and improving resource recovery. Their algorithmic approach, which combines the strengths of genetic algorithms and teaching-learning-based optimization, demonstrates a sophisticated understanding of real-world manufacturing constraints. As a scholar at the intersection of operations research and robotics, Duan is contributing to the next generation of adaptive, human-centric automation systems that promise to transform sustainable production practices.
Research Focus
Key Achievements
Top Papers
- 1