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Intuitionistic fuzzy two-sided matching model and its application to personnel-position matching problems

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  • Dejian Yu
  • Zeshui Xu

Abstract

Personnel-position matching (PPM) problems have gained wide attention from scholars in the past decades. However, the traditional matching methodologies cannot be used to solve the two-sided matching problem between personnel and position effectively. In this article, we design an intuitionistic fuzzy two-sided matching model for the PPM problem. In order to describe the correlations between the evaluated attributes, some novel intuitionistic fuzzy Choquet integral aggregation operators are proposed. The final optimal matching results can be obtained by solving the multiobjective decision-making model. A case about the PPM problem is presented to illustrate the practicality of this method. The results of this article indicate that the intuitionistic fuzzy Choquet integral aggregation operators-based two-sided matching model can effectively solve the PPM problems where their evaluated attributes are correlated.

Suggested Citation

  • Dejian Yu & Zeshui Xu, 2020. "Intuitionistic fuzzy two-sided matching model and its application to personnel-position matching problems," Journal of the Operational Research Society, Taylor & Francis Journals, vol. 71(2), pages 312-321, February.
    • Handle: RePEc:taf:tjorxx:v:71:y:2020:i:2:p:312-321
    DOI: 10.1080/01605682.2018.1546662
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    Cited by:

    1. Wei Huang & Peiqi Hu & Fu-Sheng Tsai & Yinke Liu & Yu Huang, 2022. "Smart Sales Empower Small Farmers: An Integrated Matching Method between Suppliers and Consumers Based on the Information Axiom," Sustainability, MDPI, vol. 14(24), pages 1-20, December.
    2. Mei Cai & Suqiong Hu & Ya Wang & Jingmei Xiao, 2022. "A Dynamic Social Network Matching Model for Virtual Power Plants and Distributed Energy Resources with Probabilistic Linguistic Information," Sustainability, MDPI, vol. 14(22), pages 1-33, November.

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