Husam Dauod
Papers
2
Total Citations
21
H-Index
2
About
Husam Dauod is a researcher at the intersection of operations research, automation, and healthcare logistics, with a focus on optimizing robotic dispensing systems for high-throughput pharmacy environments. His work addresses critical challenges in mail-order pharmacy automation (MOPA) facilities, where efficient replenishment and planogram design are essential for managing large prescription volumes. Dauod’s major contributions include developing a robust receding horizon control strategy for replenishment planning, which enhances the reliability and efficiency of robotic dispensing systems—a paper that has garnered 12 citations. He also pioneered a multi-objective approach that integrates association rule mining with evolutionary algorithms to optimize medication planogram layouts, achieving 9 citations. This work directly improves throughput and reduces operational bottlenecks in automated pharmacies. Dauod’s research is notable for its practical impact on healthcare supply chains, demonstrating how advanced control and optimization techniques can streamline medication dispensing, reduce errors, and lower costs. His achievements highlight a commitment to bridging theoretical optimization with real-world automation challenges, making his work valuable for researchers and practitioners in industrial engineering, healthcare systems, and robotics.
Research Focus
Key Achievements
Top Papers
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- 2