Multi-Attribute Decision-Making Based on Picture Fuzzy Einstein Operator and The TOPSIS Method

Authors

  • SITI ROHANA GOH ABDULLAH UniMAP
  • Muhammad Zaini Ahmad Institute of Engineering Mathematics, Universiti Malaysia Perlis, Perlis, Malaysia

DOI:

https://doi.org/10.58915/amci.v12i4.314

Abstract

Picture Fuzzy Sets (PFSs) denote the extension of conventional fuzzy sets, which capture a broader spectrum of human opinions, encompassing responses such as acceptance, neutrality, rejection, and hesitation. This wider range of responses cannot be accurately accommodated within fuzzy sets as well as intuitionistic fuzzy sets framework. In the realm of Multiple Attribute Group Decision-Making (MAGDM) methods, attributes frequently exhibit conflicts, uncertainties, imprecisions, as well as a lack of commensurability. To tackle the complexities inherent in MAGDM, the Technique for Order of Preference by Similarity to the Ideal Solution (TOPSIS) method has demonstrated its effectiveness. This method is employed in a compromise ranking approach founded on aggregation functions that showcase closeness to the reference points. This study's goal is to instigate a fresh approach to aggregation, referred to as the Picture Fuzzy Einstein Weighted Averaging Distance-based TOPSIS (PFEWAD-TOPSIS) method. To validate the effectiveness of this method in addressing MAGDM problems, a detailed example is conducted.

Keywords:

Picture fuzzy sets, Aggregation operator, TOPSIS, Einstein operational rule, Multi-attribute group decision making

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Published

2023-11-10

How to Cite

ABDULLAH, S. R. G., & Muhammad Zaini Ahmad. (2023). Multi-Attribute Decision-Making Based on Picture Fuzzy Einstein Operator and The TOPSIS Method. Applied Mathematics and Computational Intelligence (AMCI), 12(4), 122–139. https://doi.org/10.58915/amci.v12i4.314