Sang Won Yoon
Papers
2
Total Citations
50
H-Index
2
About
Sang Won Yoon is a leading researcher in the intersection of healthcare automation, operations research, and data mining. His primary research focuses on optimizing robotic dispensing systems (RDSs) for mail-order pharmacy automation (MOPA) facilities—high-throughput environments that process massive volumes of prescription orders. Yoon’s major contributions lie in developing data-driven methodologies to improve pharmacy efficiency and accuracy. His most cited work, “Pharmacy robotic dispensing and planogram analysis using association rule mining with prescription data” (2016, 41 citations), pioneered the use of association rule mining to analyze prescription patterns and optimize medication placement in robotic systems. He extended this research with a multi-objective approach (2018, 9 citations), integrating evolutionary algorithms to balance competing goals such as dispensing speed and inventory management. These contributions address critical challenges in automated pharmacy logistics, reducing errors and operational costs. Yoon’s work is notable for bridging advanced computational techniques with real-world healthcare applications, offering practical solutions for high-throughput fulfilment facilities. His research continues to influence the design of smarter, more efficient pharmacy automation systems, making him a key figure in healthcare operations and industrial engineering.
Research Focus
Key Achievements
Top Papers
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