A new last aggregation method of multi-attributes group decision making based on concepts of TODIM, WASPAS and TOPSIS under interval-valued intuitionistic fuzzy uncertainty

  • R. Davoudabadi
  • S. Meysam MousaviEmail author
  • V. Mohagheghi
Regular Paper


Due to the complexity of decision making under uncertainty and the existence of various and often conflicting criteria, several methods have been proposed to facilitate decision making, and fuzzy logic has been used successfully to address this issue. This paper presents a new framework for solving multi-attributes group decision-making problems under fuzzy environments. The proposed algorithm has several features. First of all, the TODIM (an acronym in Portuguese for interactive multi-criteria decision making) method under interval-valued intuitionistic fuzzy uncertainty is employed. Moreover, objective and subjective weights for each decision maker are used to address this last aggregation approach. To consider weights of attributes, knowledge measure in addition to a new mathematical approach is introduced. A new aggregation and ranking method based on the WASPAS and TOPSIS methods, namely WT method, is presented and applied in this paper. Finally, the effectiveness of the proposed framework is shown by comparing the results with two different real-world applications in the literature.


Interval-valued intuitionistic fuzzy sets (IVIFSs) Multi-attributes group decision-making (MAGDM) problems TODIM WASPAS TOPSIS Objective and subjective weights Last aggregation 



The authors would like to thank anonymous referees for their valuable comments and recommendations on this paper.

Author contributions

The authors of this research confirm the change in authorship based on their contributions in the revised version.

Compliance with ethical standards

Conflict of interest

Authors declare that they have no conflict of interest.

Informed consent

Informed consent was not required as no human or animals were involved.

Human and animal rights

This article does not contain any studies with human or animal subjects performed by any of the authors.


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Copyright information

© Springer-Verlag London Ltd., part of Springer Nature 2019

Authors and Affiliations

  • R. Davoudabadi
    • 1
  • S. Meysam Mousavi
    • 1
    Email author
  • V. Mohagheghi
    • 1
  1. 1.Department of Industrial EngineeringShahed UniversityTehranIran

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