Fuzzy Logic Applications in Computer Science and Mathematics

5A Method for Ranking Fuzzy Numbers Based on Their Value, Ambiguity, Fuzziness, and Vagueness

Sunayana Saikia* and Rituparna Chutia

Department of Mathematics, Cotton University, Guwahati, Assam, India

Abstract

Real-world issues are seen to involve uncertainty quite frequently. To prevent this uncertainty, some parameters, like fuzzy numbers, can be taken into account. As a result, ranking fuzzy numbers is crucial to bringing clarity to ambiguous situations in real life. We developed a novel fuzzy number ranking algorithm based on value, ambiguity, fuzziness, and vagueness in this study. It is discovered that the suggested ranking method has a high degree of discrimination and can rank fuzzy numbers that cannot be distinguished by other recent and established methods. Additionally, there are some numerical examples that show strong discrimination power in comparison to current approaches. The suggested method also seems to outperform in every scenario. Furthermore, the proposed strategy is applied in this work to a university/college’s assistant professor recruitment procedure for a certain field.

Keywords: Trapezoidal fuzzy numbers (TrFNs), ranking trapezoidal fuzzy numbers, value, ambiguity, fuzziness, vagueness

5.1 Introduction

Generally, generalised intervals are used to represent fuzzy numbers. As a result, fuzzy numbers cannot be ordered in the same way that real numbers can. As a result, at various times, multiple approaches for ranking fuzzy numbers have been offered. ...