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About

Mohamed Kharbeche is a leading researcher in operations research and manufacturing optimization, with a focused expertise in the Robotic Cell Problem (RCP) and its variants. His work addresses critical challenges in automated manufacturing systems by developing advanced algorithms that simultaneously schedule jobs, machines, and robotic transporters. Kharbeche’s foundational contributions include an optimization-based heuristic (2009, 43 citations) and exact methods (2010, 2011) for the classic RCP, establishing rigorous solution frameworks. His most impactful recent work tackles the RCP with Controllable Processing Times (RCPCPT), a complex real-world problem where processing speeds can be adjusted. In a 2016 paper (6 citations), he introduced a novel MIP-based heuristic and an effective genetic algorithm, while another 2016 study (5 citations) proposed a free-slack-based genetic algorithm, both achieving significant throughput optimization. Collectively, his papers have garnered over 70 citations, reflecting their influence on both theoretical research and practical manufacturing efficiency. Kharbeche’s work bridges exact optimization and metaheuristics, offering scalable solutions for modern automated production lines.