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Soft Computing

, Volume 22, Issue 22, pp 7605–7617 | Cite as

Intuitionistic linguistic group decision-making methods based on generalized compensative weighted averaging aggregation operators

  • Lidong Wang
  • Yanjun Wang
  • Arun Kumar Sangaiah
  • Binquan Liao
Methodologies and Application

Abstract

As one of the key research topic in multi-criteria group decision making (MCGDM), aggregation operator has been drawn widespread concern from academics and practitioners. In order to reflect the characteristics of human decision, it is necessary to introduce an operator with compensation ability to close the gap between the theoretical results and experimental results. Based on generalized compensative weighted averaging operator, intuitionistic linguistic generalized compensative weighted averaging (ILGCWA) operator, intuitionistic linguistic generalized compensative ordered weighted averaging (ILGCOWA) operator, and power generalized compensative weighted averaging aggregation (ILPGCWA) operator are developed in this paper. These operators provide two additional parameters to represent decision makers’ attitude and decision makers’ preference for all kinds of alternatives in the aggregation process, respectively. Moreover, some special cases with regard to the generalized parameters p and \(\lambda \) are investigated in detail in ILGCWA operator and ILGCOWA operator. Some examples are employed to illustrate the effectiveness of the proposed methods, which can be applied to solve MCGDM problem with intuitionistic linguistic information.

Keywords

Intuitionistic linguistic variable ILGCOWA operator Multi-criteria group decision making Power average (P-A) operator ILPGCWA operator 

Notes

Acknowledgements

This work was supported by the Natural Science Foundation of China (No. 61203283), Liaoning Provincial Natural Science Foundation of China (Nos. 2014025004, 201602064) and the Fundamental Research Funds for the Central Universities (Nos. 3132016306, 3132017048).

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical approval

This article does not contain any studies with human participants performed by any of the authors.

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Copyright information

© Springer-Verlag GmbH Germany 2017

Authors and Affiliations

  • Lidong Wang
    • 1
  • Yanjun Wang
    • 1
  • Arun Kumar Sangaiah
    • 2
  • Binquan Liao
    • 1
  1. 1.Department of MathematicsDalian Maritime UniversityDalianPeople’s Republic of China
  2. 2.School of Computing Science and EngineeringVIT UniversityVelloreIndia

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