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About

Dhiren Kumar Behera is a researcher specializing in Multi-Criteria Decision Making (MCDM) methodologies, with a particular focus on developing advanced hybrid decision-support systems for industrial applications. His work addresses critical challenges in engineering and operations management, including robot selection, material handling equipment (MHE) optimization, and automated system evaluation in manufacturing environments. Behera has made significant contributions by pioneering novel hybrid MCDM frameworks that integrate established techniques such as TOPSIS, COPRAS, ARAS, and Fuzzy-AHP into more robust and reliable decision-making tools. His landmark 2021 paper introducing hybrid TOPSIS-ARAS and COPRAS-ARAS models for robot selection has garnered 122 citations, reflecting its broad influence across industrial engineering and decision science communities. A companion study on material handling equipment selection using entropy-integrated COPRAS and ARAS methods further cemented his reputation, accumulating 85 citations. His 2023 work extending these frameworks through Fuzzy-AHP integration demonstrates his continued innovation in addressing real-world industrial complexity and uncertainty. Collectively, Behera's research provides practitioners and academics with powerful, practical tools for navigating complex selection problems, making him a rising and impactful voice in computational decision-making and smart manufacturing research.