Novel MCDM Methods and Similarity Measures for Extended Fuzzy Parameterized Possibility Fuzzy Soft Information with Their Applications

Abstract

Complicated uncertainties arising in the multicriteria decision-making (MCDM) problems that show distinct possible satisfaction of the subjects to favorable and equally unfavorable parameters with varying preferences require reliable decision-making under comprehensive mathematical tools. For such complications, this work aims to develop a novel fuzzy parameterized possibility fuzzy bipolar soft set model as a fuzzy parameterized bipolar soft extension of possibility fuzzy sets. The proposed model efficiently depicts the possibility of fuzzy belongingness of alternatives under fuzzy parameterized bipolar parameters (or attributes). The respective operations and properties such as subset, complement, union, and intersection are presented along with their numerical illustrations. Two logical operations namely “AND” and “OR” operations followed by two corresponding MCDM algorithms have been developed and implemented. Furthermore, similarity measures between fuzzy parameterized possibility fuzzy bipolar soft sets are proposed and applied to an agricultural land selection scenario. Finally, a comparative analysis of current work with existing ones is discussed in detail to show the eminent quality of the proposed work over them.