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About

Sadigh Raissi is a researcher specializing in robotic manufacturing cell optimization, with a particular focus on sequencing, scheduling, and operational allocation under real-world uncertainty. His work addresses the complex decision-making challenges inherent in automated production environments, where variables such as machine breakdowns, repair times, and cycle time fluctuations significantly impact efficiency and cost. Raissi's most influential contribution, "Two-Machine Robotic Cell Sequencing under Different Uncertainties" (2018, 11 citations), leverages computer simulation to tackle sequencing problems in robotic cells where uncertain parameters complicate traditional analytical approaches. Building on this foundation, his subsequent research expanded into three-machine configurations and multi-objective optimization frameworks, simultaneously minimizing cycle time and operational costs while accounting for machine availability constraints. His 2020 studies further advanced this agenda by introducing metaheuristic solution procedures, making his models computationally tractable for practical industrial application. What distinguishes Raissi's body of work is its consistent integration of mathematical programming with real-world manufacturing disruptions — a pragmatic approach that bridges theoretical optimization and applied industrial engineering. With a growing citation record across multiple publications, his research offers valuable tools for engineers and operations researchers seeking to design more resilient, cost-effective robotic manufacturing systems.