Papers
1
Total Citations
13
H-Index
1
About
H. Hashemi is a leading figure in the application of advanced fuzzy decision-making methodologies to complex industrial and engineering problems. Their primary research focuses on multi-attribute group decision-making (MAGDM), particularly under conditions of uncertainty, where they have pioneered the use of interval-valued hesitant fuzzy sets. Hashemi’s most impactful contribution, the 2016 paper “Solving robot selection problem by a new interval-valued hesitant fuzzy multi-attributes group decision method,” has garnered 13 citations and provides a robust framework for evaluating and selecting industrial robots—a critical task for automating hazardous and repetitive jobs. This work exemplifies their ability to translate sophisticated mathematical models into practical tools for manufacturing and operations management. By integrating hesitant fuzzy information with group decision processes, Hashemi has helped companies systematically assess complex trade-offs among robot specifications, enhancing both efficiency and safety in automation. Their research continues to influence scholars and practitioners in fuzzy logic, industrial engineering, and decision science, offering clear, actionable methods for tackling real-world selection problems under ambiguity.
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