Naiding Yang
Papers
4
Total Citations
86
H-Index
3
About
Naiding Yang is a researcher specializing in robotic cell scheduling, combinatorial optimization, and intelligent manufacturing systems. His work focuses on developing efficient algorithms to solve complex cyclic scheduling problems in automated robotic production environments, where minimizing cycle time and maximizing throughput are critical operational objectives. Yang's most significant contribution is his development of a branch and bound algorithm for optimal cyclic scheduling in robotic cells with processing time windows, published in 2009 and accumulating 49 citations — demonstrating its lasting influence on the field. This work provided an exact optimization framework for a problem where machines operate within flexible time constraints, advancing both theoretical formulation and practical applicability. Complementing this, his 2012 tabu search algorithm introduced innovative solution space partitioning and repairing procedures to tackle the NP-hard nature of cyclic robotic scheduling, earning 27 citations for its heuristic sophistication. Yang has also contributed exact algorithmic approaches for flexible processing time scenarios and explored genetic algorithm enhancements to overcome common convergence limitations. Collectively, his research bridges exact and metaheuristic methods, offering a comprehensive toolkit for industrial scheduling challenges. His body of work serves as a valuable reference for researchers and practitioners designing optimized robotic manufacturing workflows.
Research Focus
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