Complex intuitionistic fuzzy Maclaurin symmetric mean operators and its application to emergency program selection

Author:

Ali Riaz1,Abdullah Saleem1,Muhammad Shakoor1,Naeem Muhammad2,Chinram Ronnason3

Affiliation:

1. Department of Mathematics, Abdul Wali KhanUniversity Mardan, Mardan KPK, Pakistan

2. Deanship of Combined First Year, Umm Al-Qura University, Makkah, Saudi Arabia

3. Division of Computational Science, Facultyof Science, Prince of Songkla University, Hat Yai, Songkhla, Thailand

Abstract

Due to the indeterminacy and uncertainty of the decision-makers (DM) in the complex decision making problems of daily life, evaluation and aggregation of the information usually becomes a complicated task. In literature many theories and fuzzy sets (FS) are presented for the evaluation of these decision tasks, but most of these theories and fuzzy sets have failed to explain the uncertainty and vagueness in the decision making issues. Therefore, we use complex intuitionistic fuzzy set (CIFS) instead of fuzzy set and intuitionistic fuzzy set (IFS). A new type of aggregation operation is also developed by the use of complex intuitionistic fuzzy numbers (CIFNs), their accuracy and the score functions are also discussed in detail. Moreover, we utilized the Maclaurin symmetric mean (MSM) operator, which have the ability to capture the relationship among multi-input arguments, as a result, CIF Maclarurin symmetric mean (CIFMSM) operator and CIF dual Maclaurin symmetric mean (CIFDMSM) operator are presented and their characteristics are discussed in detail. On the basis of these operators, a MAGDM method is presented for the solution of group decision making problems. Finally, the validation of the propounded approach is proved by evaluating a numerical example, and by the comparison with the previously researched results.

Publisher

IOS Press

Subject

Artificial Intelligence,General Engineering,Statistics and Probability

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