Abdul Razak Kaladgi
Papers
1
Total Citations
122
H-Index
1
About
Abdul Razak Kaladgi is a prominent researcher in the field of Multi-Criteria Decision Making (MCDM), with a focus on developing advanced hybrid models to solve complex industrial and engineering selection problems. His major contribution lies in pioneering novel combinations of traditional MCDM techniques—such as TOPSIS, ARAS, and COPRAS—to create more robust and accurate decision-support systems. His most-cited work, "Analysis of a Robot Selection Problem Using Two Newly Developed Hybrid MCDM Models of TOPSIS-ARAS and COPRAS-ARAS" (2021), has garnered 122 citations, reflecting its significant impact on both academia and industry. This study addressed the critical need for modernizing outdated MCDM approaches by integrating multiple methods, thereby enhancing reliability in real-world applications like robot selection. Kaladgi’s research is instrumental for students and practitioners seeking efficient, data-driven solutions to intricate decision-making challenges, solidifying his reputation as an innovator in operational research and applied mathematics.
Research Focus
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Top Papers
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