Farzad Tahriri

Papers

Total Citations

160

H-Index

About

Farzad Tahriri is a researcher at the forefront of manufacturing systems optimization, with a primary focus on flexible manufacturing systems (FMS), robotics, and advanced scheduling algorithms. His most influential work, a 2017 study on multi-objective AGV scheduling in an FMS, has garnered 135 citations. In this paper, Tahriri pioneered a hybrid approach combining genetic algorithms with particle swarm optimization to solve complex scheduling problems, directly addressing the manufacturing industry's need for greater flexibility and responsiveness to fluctuating customer demand. His research demonstrates that the performance of an FMS hinges critically on precise scheduling policies for system components like automated guided vehicles. Tahriri has also made notable contributions to robotics, optimizing robot arm movement time using virtual reality teaching systems—a 2015 study with 25 citations that minimizes make-span and maximizes production rates in operations such as welding and drilling. By bridging virtual reality with robotic programming, his work reduces programming complexity while enhancing efficiency. Tahriri’s research is essential reading for students and engineers seeking to understand how intelligent algorithms and immersive technologies can transform modern manufacturing into a more agile, productive, and responsive enterprise.