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Selection of Academic Staff Based on a Hybrid Multi-criteria Decision Method Under Neutrosophic Environment

Author

Listed:
  • Antonios Paraskevas

    (University of Macedonia)

  • Michael Madas

    (University of Macedonia)

Abstract

Multi-criteria decision-making (MCDM) is a decision-making process that involves assessing and selecting the best alternative from a group of options based on various criteria or qualities. In this research work, we propose and elucidate the theory of neutrosophic logic, which is unique in its approach to evaluating candidates’ performance in a manner that takes into account significant elements and criteria that are essential for the overall process when dealing with unclear, inaccurate, or incomplete data. We propose a novel hybrid integrated MCDM methodology based upon neutrosophic Delphi (N-Delphi) and neutrosophic AHP (N-AHP) methods, which takes into consideration the importance of each decision-maker and their preferences per evaluation criterion. A new MAXMIN threshold value technique treats the criteria under consideration as the decision alternatives and their score functions as their payoff values, thus reducing unnecessary resources by eliminating unimportant criteria during the personnel selection process.

Suggested Citation

  • Antonios Paraskevas & Michael Madas, 2024. "Selection of Academic Staff Based on a Hybrid Multi-criteria Decision Method Under Neutrosophic Environment," SN Operations Research Forum, Springer, vol. 5(1), pages 1-27, March.
    • Handle: RePEc:spr:snopef:v:5:y:2024:i:1:d:10.1007_s43069-024-00309-9
    DOI: 10.1007/s43069-024-00309-9
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    References listed on IDEAS

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    1. Thomas L. Saaty & Luis G. Vargas, 2006. "Decision Making with the Analytic Network Process," International Series in Operations Research and Management Science, Springer, number 978-0-387-33987-0, December.
    2. Opricovic, Serafim & Tzeng, Gwo-Hshiung, 2004. "Compromise solution by MCDM methods: A comparative analysis of VIKOR and TOPSIS," European Journal of Operational Research, Elsevier, vol. 156(2), pages 445-455, July.
    3. Canós, L. & Liern, V., 2008. "Soft computing-based aggregation methods for human resource management," European Journal of Operational Research, Elsevier, vol. 189(3), pages 669-681, September.
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