Abstract We define 2 n+ 1 2 n+ 1 and 2 n fuzzy numbers, which generalize triangular and
trapezoidal fuzzy numbers, respectively. Then, we extend the fuzzy preference relation and …

In this paper, we first propose a fuzzy preference relation with membership function
representing preference degree to compare two fuzzy numbers. Then a relative preference …

Generally, classical multi-criteria decision-making (MCDM) methods were extended to
encompass uncertainty and vagueness of messages under fuzzy environment for solving …

In fuzzy decision problems, the ordering of fuzzy numbers is the basic problem. The fuzzy
preference relation is the reasonable representation of preference relations by a fuzzy …

The final values of alternatives usually are fuzzy numbers in most decision making problems
under uncertain environment. These fuzzy numbers need to be defuzzified by a ranking …

The problem (or scenario) involving qualitative or imprecise information is not solvable by
classical set theory. To overcome the shortcoming of classical set theory, Zadeh (Inf Control …

In this paper, we consider the factor of the decision maker's risk preference, and define the
left and right deviation degree respectively. Besides, we propose a new formula of the fuzzy …

In this paper, we introduce the concept of triangular cubic fuzzy numbers. We discuss some
basic operational laws of triangular cubic fuzzy numbers and then develop triangular cubic …

Ranking of fuzzy numbers is an inevitable task in solving multi-criteria decision-making
problems modelling under a fuzzy environment. Generalized trapezoidal fuzzy numbers are …

In this paper, we propose a novel method for ranking fuzzy numbers based on additively
consistent fuzzy preference relations (ACFPR). We introduce the so-called additive priority …