Masoud Shafipour

Mazandaran University of Science and Technology

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About

Masoud Shafipour is a prominent researcher in operations research and industrial engineering, with a primary focus on scheduling and optimization. His work centers on developing efficient metaheuristic algorithms to solve complex, resource-constrained scheduling problems, particularly in parallel machine environments with practical constraints like machine eligibility restrictions. His most cited paper, "Design of an efficient genetic algorithm for resource-constrained unrelated parallel machine scheduling problem with machine eligibility restrictions" (2015), has garnered 83 citations, underscoring its influence in advancing algorithmic solutions for real-world manufacturing and production systems. Shafipour’s contributions are notable for bridging theoretical optimization with practical industrial applications, offering robust methods that improve efficiency and resource utilization. His research has been widely recognized for its impact on the field of scheduling, providing a foundation for subsequent studies in metaheuristics and combinatorial optimization. Through his work, Shafipour has established himself as a key figure in the development of intelligent scheduling systems, making significant strides in enhancing productivity and decision-making in complex operational environments.