• COMPARATIVE STUDY OF BIPOLAR FUZZY SOFT CATEGORY ACTION FOR ASSISTANT PROFESSOR RECRUITMENT IN GOVERNMENT SECTORS

Abstract

The Bipolar fuzzy soft techniques represent the recruitment of Assistant Professor as a multi-criteria group decision making process which involves subjectivity, imprecision and fuzziness. Here we have applied the score and accuracy functions, the hybrid score accuracy functions of bipolar fuzzy soft numbers (BFSNS) and ranking method for BFSNS. To rank the alternatives and recruit the most desirable professors, we use the overall evaluation formula of the weighted hybrid score accuracy functions for each alternative. To illustrate the effectiveness of the proposed model, the education problem for assistant professor selection is provided. Therefore we compare this result with TOPGREY Algorithm.