A Novel MADM Framework under q -Rung Orthopair Fuzzy Bipolar Soft Sets

Ghous Ali, Hanan Alolaiyan, Dragan Pamučar, Muhammad Asif and Nimra Lateef
Additional contact information
Ghous Ali: Department of Mathematics, Division of Science and Technology, University of Education, Lahore 54770, Pakistan
Hanan Alolaiyan: Department of Mathematics, King Saud University, Riyadh 11451, Saudi Arabia
Dragan Pamučar: Department of Logistics, Military Academy, University of Defence in Belgrade, 11000 Belgrade, Serbia
Muhammad Asif: School of Mathematics, Xiamen University, Xiamen 361005, China
Nimra Lateef: Department of Mathematics, Division of Science and Technology, University of Education, Lahore 54770, Pakistan

Mathematics, 2021, vol. 9, issue 17, 1-22

Abstract: In many real-life problems, decision-making is reckoned as a powerful tool to manipulate the data involving imprecise and vague information. To fix the mathematical problems containing more generalized datasets, an emerging model called q -rung orthopair fuzzy soft sets offers a comprehensive framework for a number of multi-attribute decision-making (MADM) situations but this model is not capable to deal effectively with situations having bipolar soft data. In this research study, a novel hybrid model under the name of q -rung orthopair fuzzy bipolar soft set ( q -ROFBSS, henceforth), an efficient bipolar soft generalization of q -rung orthopair fuzzy set model, is introduced and illustrated by an example. The proposed model is successfully tested for several significant operations like subset, complement, extended union and intersection, restricted union and intersection, the ‘AND’ operation and the ‘OR’ operation. The De Morgan’s laws are also verified for q -ROFBSSs regarding above-mentioned operations. Ultimately, two applications are investigated by using the proposed framework. In first real-life application, the selection of land for cropping the carrots and the lettuces is studied, while in second practical application, the selection of an eligible student for a scholarship is discussed. At last, a comparison of the initiated model with certain existing models, including Pythagorean and Fermatean fuzzy bipolar soft set models is provided.

Keywords: q-rung orthopair fuzzy soft set; bipolar soft set; score function; algorithm; decision-making (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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