Bonferroni Mean Operators Based on Interval-Valued Picture Hesitant Fuzzy Information and Their Application in Decision-Making Problems

Zeeshan Ali; Tahir  Mahmood

doi:10.47852/bonviewJCCE3202951

Authors

Zeeshan Ali Department of Mathematics and Statistics, International Islamic University, Pakistan
Tahir Mahmood Department of Mathematics and Statistics, International Islamic University, Pakistan https://orcid.org/0000-0002-3871-3845

DOI:

https://doi.org/10.47852/bonviewJCCE3202951

Keywords:

picture fuzzy sets, hesitant fuzzy sets, interval-valued picture hesitant fuzzy sets, Bonferroni mean operators, multi-attribute decision-making techniques

Abstract

In this article, we invent the Bonferroni mean (BM) operators using interval-valued picture hesitant fuzzy (IVPHF) technique, called IVPHF Bonferroni mean (IVPHFBM), IVPHF-weighted BM (IVPHFWBM), IVPHF geometric BM (IVPHFGBM), and IVPHF-weighted geometric BM (IVPHFWGBM) operators. These presented techniques are very beneficial and valuable because these are modified versions of many existing techniques. Moreover, we also examine three basic properties of each presented operator. In addition, we demonstrate the technique of multi-attribute decision-making (MADM) problem and try to describe it with the presence of evaluated techniques to show the capability and superiority of the invented theory. In last, we compare the prevailing techniques with presented studies to illustrate the supremacy and effectiveness of the derived approaches.

Received: 10 April 2023 | Revised: 15 May 2023 | Accepted: 25 May 2023

Conflicts of Interest

The authors declare that they have no conflicts of interest to this work.

Data Availability Statement

Data sharing is not applicable to this article as no new data were created or analyzed in this study.