Decision-Making Approach with Complex Bipolar Fuzzy N-Soft Sets

Author:

Farooq Adeel1ORCID,Ali Al-Shamiri Mohammed M.23ORCID,Khalaf Mohammed M.4,Amjad Umaira5

Affiliation:

1. Department of Mathematics, COMSATS University Islamabad, Lahore Campus, Lahore 54590, Pakistan

2. Department of Mathematics, Faculty of Science and Arts, King Khalid University, Muhayl Assir, Saudi Arabia

3. Department of Mathematics and Computer, Faculty of Science, Ibb University, Ibb, Yemen

4. Faculty of Engineering, Arab Academy for Science & Technology and Maritime Transport (AASTMT), Aswan Branch, Egypt

5. Department of Mathematics, University of the Punjab, New Campus, Lahore, Pakistan

Abstract

The primary aim of this article is to extend the bipolar fuzzy N -soft sets with the concern of pursuing the periodicity involved real-world problems and introduce a new multiskilled hybrid model, namely, complex bipolar fuzzy N -soft sets. The novel model possesses the parametric characteristics of the versatile N -soft set and enjoys the distinguished attributes of a complex bipolar fuzzy set to handle the double-sided periodic vague data. We illustrate that the innovative model assists as a proficient mechanism for grading-based parameterized two-dimensional bipolar fuzzy information. We present some elementary operations and results for a complex bipolar fuzzy N -soft environment. Further, we establish the three dexterous algorithms to find the optimal solution to multiattribute decision-making problems. Moreover, the algorithms are supported with the robust assessment of a real-world application. Lastly, a comparison with existent decision-making techniques, such as choice values, weighted choice values, and D -choice of values of bipolar fuzzy N -soft sets, is also conducted to manifest the phenomenal accountability and authenticity of the presented decision-making approaches.

Funder

King Khalid University

Publisher

Hindawi Limited

Subject

General Engineering,General Mathematics

Reference26 articles.

1. Fuzzy sets

2. Intuitionistic fuzzy sets

3. Bipolar fuzzy sets and relations: a computational framework for cognitive modeling and multiagent decision analysis;W.-R. Zhang

4. Complex fuzzy sets

5. Graphs for the Analysis of Bipolar Fuzzy Information

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