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Three-Dimensional Interval-Valued Intuitionistic Fuzzy Appointment Model

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Recent Advances in Computational Optimization

Part of the book series: Studies in Computational Intelligence ((SCI,volume 838))

Abstract

The paper explores the process of appointment of positions in an organization in conditions of uncertainty. We extend the optimization problem [28] of the process of appointment and reappointment, based on  partial knowledge about the values of evaluation criteria of the human resources over time. Here, the 3-dimensional optimal appointment problem is formulated and an algorithm for its optimal solution is proposed, where the evaluations of candidates against criteria formulated by several experts at a fixed time, are interval-valued intuitionistic fuzzy pairs (IVIFPs). The proposed algorithm for the solution takes into account the ratings of the experts and the weight coefficients of the assessment criteria according to their priority for the respective position.

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Acknowledgements

This work was supported by the Bulgarian Ministry of Education and Science under the National Research Programme “Young scientists and postdoctoral students”, approved by DCM # 577/ 17.08.2018.

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Authors and Affiliations

  1. “Prof. Asen Zlatarov” University, “Prof. Yakimov” Blvd, 8000, Bourgas, Bulgaria

    Velichka Traneva & Stoyan Tranev

  2. Institute of Biophysics and Biomedical Engineering, Bulgarian Academy of Sciences, 105 “Acad. G. Bonchev” Str., 1113, Sofia, Bulgaria

    Vassia Atanassova

Authors
  1. Velichka Traneva
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  2. Vassia Atanassova
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  3. Stoyan Tranev
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Corresponding author

Correspondence to Velichka Traneva .

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Editors and Affiliations

  1. Parallel Algorithms, Institute of Information and Communication Technology, Bulgarian Academy of Sciences, Sofia, Bulgaria

    Stefka Fidanova

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Traneva, V., Atanassova, V., Tranev, S. (2020). Three-Dimensional Interval-Valued Intuitionistic Fuzzy Appointment Model. In: Fidanova, S. (eds) Recent Advances in Computational Optimization. Studies in Computational Intelligence, vol 838. Springer, Cham. https://doi.org/10.1007/978-3-030-22723-4_12

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