Prasad Karande
Papers
6
Total Citations
171
H-Index
5
About
Prasad Karande is a leading researcher in multicriteria decision-making (MCDM), with a special focus on industrial robot selection and nontraditional machining processes. His work systematically evaluates and enhances the ranking performance of popular MCDM methods—such as WSM, WPM, WASPAS, and ELECTRE-I—under complex, multipolar uncertainty conditions. Karande’s most cited paper (126 citations) provides a rigorous comparative study of six MCDM methods for robot selection, establishing a benchmark for practitioners. He has since pioneered the integration of m-polar fuzzy sets with ELECTRE-I algorithms, addressing real-world problems where data involves multiple, conflicting criteria. His contributions include analyzing the impact of normalization techniques and criteria weight calculations on rank stability, as well as developing novel performance score approaches. With over 170 citations across his key works, Karande’s research directly supports engineers and decision-makers in manufacturing, automation, and process selection. His work is notable for bridging theoretical MCDM advancements with practical, high-stakes industrial applications, making him a valuable resource for students and researchers seeking robust, uncertainty-aware decision tools.
Research Focus
Key Achievements
Top Papers
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- 4Rank Assessment of Robots Using m-Polar Fuzzy ELECTRE-I Algorithm8 citations · 2021
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