Generalized Fuzzy Soft Power Bonferroni Mean Operators and Their Application in Decision Making

Abstract

In decision-making process, decision-makers may make different decisions because of their different experiences and knowledge. The abnormal preference value given by the biased decision-maker (the value that is too large or too small in the original data) may affect the decision result. To make the decision fair and objective, this paper combines the advantages of the power average (PA) operator and the Bonferroni mean (BM) operator to define the generalized fuzzy soft power Bonferroni mean (GFSPBM) operator and the generalized fuzzy soft weighted power Bonferroni mean (GFSWPBM) operator. The new operator not only considers the overall balance between data and information but also considers the possible interrelationships between attributes. The excellent properties and special cases of these ensemble operators are studied. On this basis, the idea of the bidirectional projection method based on the GFSWPBM operator is introduced, and a multi-attribute decision-making method, with a correlation between attributes, is proposed. The decision method proposed in this paper is applied to a software selection problem and compared to the existing methods to verify the effectiveness and feasibility of the proposed method.

Generalized Orthopair Fuzzy Weighted Power Bonferroni Mean Operator and Its Application in Decision Making

“…For instance, Garg [38] proposed a multi-attribute decision-making algorithm based on trigonometric generalized orthopair fuzzy numbers. Xu et al [39] introduced a multi-attribute decision-making method based on fuzzy soft sets. Chen et al [40] put forward a multi-attribute decision-making model based on the intuitionistic trapezoidal fuzzy generalized Heronian OWA operator, and Li et al [41] proposed a series of multiattribute decision-making methods based on the Pythagorean fuzzy power Muirhead mean operators.…”