Muhammad Muneeb ul Hassan
Papers
1
Total Citations
17
H-Index
1
About
Muhammad Muneeb ul Hassan is a rising scholar in the field of decision science and industrial engineering, with a focused expertise in multi-criteria decision-making (MCDM) under uncertainty. His research centers on developing hybrid mathematical models that integrate fuzzy set theory with advanced MCDM techniques to solve complex, real-world selection problems. His most cited work, "Enhancing industrial robot selection through a hybrid novel approach: integrating CRITIC-VIKOR method with probabilistic uncertain linguistic q-rung orthopair fuzzy" (2024, 17 citations), exemplifies his core contribution: creating robust frameworks that help decision-makers navigate ambiguous and conflicting attributes when choosing sophisticated industrial equipment. By introducing novel probabilistic uncertain linguistic q-rung orthopair fuzzy sets, he has advanced the theoretical toolkit for handling vagueness in expert judgments. While still early in his career, his work is gaining traction for its practical applicability in manufacturing and technology selection. His research bridges the gap between theoretical fuzzy mathematics and actionable industrial decision-making, offering a systematic pathway for optimizing choices under uncertainty.
Research Focus
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Top Papers
- 1