Abstract: The rapidly evolving nature of uncertainty issues requires researchers to continuously develop current mathematical tools. For example, employee selection techniques in government institutions are subject to rigorous evaluation by human resources department committees, during which positive and negative impressions are formed when interviewing candidates applying for these jobs. Therefore, in order to cover this impression, we will present in this work a mathematical model called bipolar fuzzy soft, associated with the influence of interval form. This model study translates positive and negative thinking into an interval degree of ambiguity ranging between [0,1] for the positive side and an interval degree ranging between [-1,0] for the negative side. On BIV-FSS, we define and study basic set operations, including the extended union, intersection of two BIV-FSSs, and the complement operation of BIV-FSS. Some properties and numerical examples that illustrate. Finally, we will demonstrate the practical side of this work by presenting a new algorithm that relies on the tools proposed in this work to solve one of the decision-making problems in the administrative aspect (employee selection).

Keywords: Bipolar fuzzy set, Bipolar fuzzy soft set, Interval valued fuzzy set, Interval valued bipolar fuzzy set, Decision-making

Pages: 179-190