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Multiple Attribute Group Decision-Making Based on Power Heronian Aggregation Operators under Interval-Valued Dual Hesitant Fuzzy Environment

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  • Shenqing Jiang
  • Wei He
  • Fangfang Qin
  • Qingqing Cheng

Abstract

In this paper, we focus on new methods to deal with multiple attribute group decision-making (MAGDM) problems and a new comparison law of interval-valued dual hesitant fuzzy elements (IVDHFEs). More explicitly, the interval-valued dual hesitant fuzzy 2nd-order central polymerization degree ( ) function is introduced, for the case that score values of different IVDHFEs are identical. This function can further compare different IVDHFEs. Then, we develop a series of interval-valued dual hesitant fuzzy power Heronian aggregation operators, i.e., the interval-valued dual hesitant fuzzy power Heronian mean (IVDHFPHM) operator, the interval-valued dual hesitant fuzzy power geometric Heronian mean (IVDHFPGHM) operator, and their weighted forms. Some desirable properties and their special cases are discussed. These proposed operators can simultaneously reflect the interrelationship of aggregated arguments and reduce the influence of unreasonable evaluation values. Finally, two approaches for interval-valued dual hesitant fuzzy MAGDM with known or unknown weight information are presented. An illustrative example and comparative studies are given to verify the advantages of our methods. A sensitivity analysis of the decision results is analyzed with different parameters.

Suggested Citation

  • Shenqing Jiang & Wei He & Fangfang Qin & Qingqing Cheng, 2020. "Multiple Attribute Group Decision-Making Based on Power Heronian Aggregation Operators under Interval-Valued Dual Hesitant Fuzzy Environment," Mathematical Problems in Engineering, Hindawi, vol. 2020, pages 1-19, June.
  • Handle: RePEc:hin:jnlmpe:2080413
    DOI: 10.1155/2020/2080413
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    Cited by:

    1. Ximei Hu & Shuxia Yang & Ya-Ru Zhu, 2021. "Multiple Attribute Decision-Making Based on Three-Parameter Generalized Weighted Heronian Mean," Mathematics, MDPI, vol. 9(12), pages 1-29, June.

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