Papers

19

Total Citations

189

H-Index

8

About

Shujin Qin is a researcher specializing in sustainable manufacturing, disassembly line optimization, and human-robot collaboration, with a particular focus on solving complex combinatorial problems that arise in end-of-life product recycling and remanufacturing. His work addresses a critical challenge at the intersection of robotics, operations research, and environmental engineering: how to efficiently disassemble obsolete products to minimize waste, reduce energy consumption, and recover valuable resources. Qin's most significant contributions lie in developing and applying advanced metaheuristic algorithms — including multi-objective shuffled frog leaping, multiverse optimization, and ant lion optimization methods — to tackle increasingly realistic disassembly line balancing problems. His highly cited 2023 paper on human-robot collaborative disassembly under stochastic operation times (69 citations) demonstrates his ability to model real-world uncertainty while optimizing multiple competing objectives simultaneously. Subsequent work has expanded these frameworks to U-shaped lines, multi-product scenarios, parallel workstations, and resource-sharing configurations, reflecting a systematic deepening of the field. With over 160 cumulative citations across his published works, Qin has established himself as a productive contributor to green manufacturing research. His research is particularly valuable for engineers and operations researchers seeking intelligent, computationally efficient solutions to the growing global challenge of sustainable product end-of-life management.

Research Focus

Key Achievements

8
H-Index
19
Papers
189
Total Citations
10
Avg Citations/Paper
🏆 Most Cited Paper
Human–Robot Collaborative Disassembly Line Balancing Problem With Stochastic Operation Time and a Solution via Multi-Objective Shuffled Frog Leaping Algorithm
69 citations · 2023
📈 Most Prolific Year: 2022 (6 Papers)
🤝 Key Collaborators: 30
🏛 Institutions: Shangqiu Normal University, Liaoning Shihua University

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
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