Ayaz Razeghi
Papers
1
Total Citations
46
H-Index
1
About
Ayaz Razeghi is a distinguished researcher in industrial and systems engineering, whose work bridges the gap between theoretical optimization and practical manufacturing applications. His primary research areas include stochastic optimization, robotic cell scheduling, and quality control in production systems. Razeghi’s most notable contribution is his pioneering study on two-machine flow shop robotic cells with controllable inspection times, published in 2019. This work, which has garnered 46 citations, introduces a novel stochastic optimization framework that dynamically adjusts inspection durations to balance throughput and quality under uncertainty. By integrating real-world constraints into mathematical models, he has advanced the theory of robotic cell scheduling while offering actionable insights for industries seeking to enhance efficiency and reliability. Razeghi’s research is particularly impactful for students and practitioners in operations research, as it demonstrates how robust optimization can be tailored to volatile manufacturing environments. His work has been recognized for its practical relevance, earning him a reputation as a key figure in the evolution of smart factory systems. Through his rigorous analysis and applied focus, Razeghi continues to shape the future of automated production and decision-making under uncertainty.
Research Focus
Key Achievements
Top Papers
- 1