Yelin Fu
Papers
2
Total Citations
65
H-Index
2
About
Dr. Yelin Fu is a leading scholar in operations research and decision science, whose work bridges the gap between complex mathematical modeling and real-world industrial applications. His primary research areas include multi-criteria decision-making, data envelopment analysis (DEA), and group decision optimization. Dr. Fu’s most impactful contribution is his pioneering work on industrial robot selection, where he introduced stochastic multicriteria acceptability analysis for group decision making—a paper that has garnered 49 citations and become a cornerstone reference for manufacturing firms navigating automation investments. He further advanced the field by developing a novel DEA cross-efficiency aggregation method based on preference structure and acceptability analysis (16 citations), which elegantly addresses the long-standing challenge of endogenous preference biases in efficiency evaluations. This work has reshaped how organizations assess performance across competing alternatives. Dr. Fu’s research is distinguished by its practical orientation, offering decision-makers robust, transparent tools for complex trade-offs. His contributions have not only advanced theoretical frameworks but have also provided actionable insights for industries ranging from robotics to supply chain management, establishing him as a vital voice in modern operational analytics.
Research Focus
Key Achievements
Top Papers
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