Complex Polytopic Fuzzy Model and Their Induced Aggregation Operators

Journal Title: Acadlore Transactions on Applied Mathematics and Statistics - Year 2024, Vol 2, Issue 1

Abstract

Inducing variables are the parameters or conditions that influence the membership value of an element in a fuzzy set. These variables are often linguistic in nature and represent qualitative aspects of the problem. Thus, the objective of this paper is introduce some aggregation operators based on inducing variable, such as induced complex Polytopic fuzzy ordered weighted averaging aggregation operator (I-CPoFOWAAO) and induced complex Polytopic fuzzy hybrid averaging aggregation operator (I-CPoFHAAO). Induced aggregation operators in decision-making process are indispensable tools for managing uncertainty, integrating multiple criteria, facilitating consensus, and providing a formal and flexible framework for modeling and solving complex decision problems. At the end of the paper, we make an illustrative example to prove the ability and efficiency of the novel proposed aggregation operators.

Authors and Affiliations

Khaista Rahman, Jan Muhammad

Keywords

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  • EP ID EP732913
  • DOI 10.56578/atams020104
  • Views 38
  • Downloads 0

How To Cite

Khaista Rahman, Jan Muhammad (2024). Complex Polytopic Fuzzy Model and Their Induced Aggregation Operators. Acadlore Transactions on Applied Mathematics and Statistics, 2(1), -. https://europub.co.uk/articles/-A-732913