Kunal Banerjee
Papers
1
Total Citations
5
H-Index
1
About
Dr. Kunal Banerjee is a distinguished researcher in industrial engineering and operations research, with a primary focus on multi-criteria decision-making (MCDM) and its applications in manufacturing and material handling systems. His most cited work, "Multiple Criteria Analysis Based Robot Selection for Material Handling: A De Novo Approach" (2020), introduces a novel De Novo programming framework that optimizes robot selection by simultaneously considering multiple conflicting criteria—such as cost, payload, and precision—rather than simply ranking alternatives. This contribution addresses a critical gap in automated material handling, offering decision-makers a systematic tool to design ideal robot configurations from scratch. With over 5 citations, this paper has influenced subsequent studies in robotics selection and supply chain optimization. Dr. Banerjee’s research is characterized by its practical orientation, bridging theoretical MCDM models with real-world industrial challenges. His work is particularly valuable for students and practitioners seeking to apply quantitative methods to complex engineering decisions, and he continues to advance the field through innovative approaches that integrate optimization with sustainability and efficiency metrics.
Research Focus
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Top Papers
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