Seyed Meysam Mousavi
Papers
6
Total Citations
414
H-Index
6
About
Seyed Meysam Mousavi is a prominent researcher specializing in fuzzy decision-making, multi-criteria decision analysis, and soft computing, with a particular focus on solving complex industrial selection and optimization problems under uncertainty. His work has made significant contributions to the development and refinement of advanced fuzzy methodologies, most notably through his highly cited 2011 paper on a novel fuzzy modified TOPSIS method for group decision making, which has garnered 168 citations and stands as a foundational reference in the field. Mousavi has consistently pushed the boundaries of classical decision-making frameworks by incorporating interval-valued fuzzy sets and hesitant fuzzy environments, enabling more realistic modeling of expert uncertainty and linguistic ambiguity. His research portfolio includes innovative applications to robot selection, a challenging industrial problem requiring the evaluation of complex technical specifications across multiple competing criteria. With a growing body of work accumulating over 400 citations collectively, Mousavi's contributions have proven highly valuable to engineers, operations researchers, and decision scientists seeking robust, mathematically grounded tools for tackling real-world industrial challenges where precise data is rarely available.
Research Focus
Key Achievements
Top Papers
- 1Group decision making based on novel fuzzy modified TOPSIS method168 citations · 2011
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