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Robust Aggregation Operators for Intuitionistic Fuzzy Hypersoft Set With Their Application to Solve MCDM Problem.

Rana Muhammad ZulqarnainImran SiddiqueRifaqat AliDragan PamucarDragan MarinkovicDarko Božanić
Published in: Entropy (Basel, Switzerland) (2021)
In this paper, we investigate the multi-criteria decision-making complications under intuitionistic fuzzy hypersoft set (IFHSS) information. The IFHSS is a proper extension of the intuitionistic fuzzy soft set (IFSS) which discusses the parametrization of multi-sub attributes of considered parameters, and accommodates more hesitation comparative to IFSS utilizing the multi sub-attributes of the considered parameters. The main objective of this research is to introduce operational laws for intuitionistic fuzzy hypersoft numbers (IFHSNs). Additionally, based on developed operational laws two aggregation operators (AOs), i.e., intuitionistic fuzzy hypersoft weighted average (IFHSWA) and intuitionistic fuzzy hypersoft weighted geometric (IFHSWG), operators have been presented with their fundamental properties. Furthermore, a decision-making approach has been established utilizing our developed aggregation operators (AOs). Through the established approach, a technique for solving decision-making (DM) complications is proposed to select sustainable suppliers in sustainable supply chain management (SSCM). Moreover, a numerical description is presented to ensure the validity and usability of the proposed technique in the DM process. The practicality, effectivity, and flexibility of the current approach are demonstrated through comparative analysis with the assistance of some prevailing studies.
Keyphrases
  • decision making
  • neural network
  • magnetic resonance
  • magnetic resonance imaging
  • health information
  • healthcare
  • computed tomography
  • network analysis
  • adipose tissue
  • glycemic control
  • insulin resistance
  • weight loss