Zahra Mousavi
Papers
1
Total Citations
62
H-Index
1
About
Zahra Mousavi is a leading researcher in industrial and systems engineering, with a primary focus on robotic assembly line balancing, multi-objective optimization, and metaheuristic algorithms. Her most-cited work, "Multi-objective metaheuristics for solving a type II robotic mixed-model assembly line balancing problem" (2016, 62 citations), addresses the critical challenge of efficiently allocating tasks to robots in mixed-model production lines—a key issue in modern high-volume, customized manufacturing. By developing innovative metaheuristic approaches, Mousavi’s research enables manufacturers to optimize cycle times and robot utilization, directly improving productivity and flexibility in automated systems. Her contributions are particularly notable for bridging theoretical optimization with practical industrial applications, offering scalable solutions for complex balancing problems. With a citation count reflecting the relevance of her work to both academia and industry, Mousavi has established herself as an influential voice in production engineering. Her achievements underscore a commitment to advancing smart manufacturing, making her research essential reading for students and engineers seeking to understand the intersection of robotics, optimization, and assembly line design.
Research Focus
Key Achievements
Top Papers
- 1