Schweizer-Sklar prioritized aggregation operators for intuitionistic fuzzy information and their application in multi-attribute decision-making

Abstract

The theory of SS t-norm and t-conorm was derived by Schweizer and Sklar in 1960 by involving a parameter Γ¯¯, which are more flexible and valuable to manage awkward and vague data. with the help of parameter Γ¯¯=-1,1, we can easily derive the information of Hamacher and Lukasiewicz t-norms. Moreover, a prioritized aggregation operators (PAOs) are also used for determining the collection of information into a singleton set. The key impact of this study is to derive the PAOs based on SS t-norm and t-conorm for IF information and hence derive some new aggregation operators. The fundamental properties of the stated operators are also discovered. Additionally, we derived some valuable characteristics of the above-presented operators and pioneered a MADM (“multi attribute decision-making”) tool to handle the unreliable and vague types of information with the help of proposed operators. Finally, with the help of a practical example, we derived that the proposed MADM algorithm is massive superior then the prevailing operators by doing the comparison between pioneered and existing approaches to enhance the capability and worth of the diagnosed operators.

Cite this work

No public copy is stored for this record, so only the metadata is cited.

Stored only when both papers are in the corpus — 70 citations exist upstream.

Papers that cite the same references — the relational fallback while embeddings are still backfilling.