The probabilistic linguistic term sets (PLTSs) allow experts to express their preferences regarding one over another. Nowadays, multicriteria decision-making methods for PLTSs are very popular, and Bai et al's method based on the possibility degree formula cannot be ranked in some situations. In this paper, we first propose a new state properties, use solve drawbacks of method. Second, weight average (PLWA) order (PLOWA) operator properties. Then, PLWA operator, operator. Finally, utilize an...

The probabilistic linguistic term sets (PLTSs) allow experts to express their preferences on one over another. However, when the probability of given is internal number nor numerical value. PLTS no way it. Therefore, Bai et al. proposed definiti uncertain set (UPLTS). In this paper, we first propose a priority degree method for interval and possibility PLTS. Second, based above mentioned two methods, new UPLTS solve problem al's method. Third, aggregation operators UPLTSs, which are...

In this paper, the concept of 2-tuple probability weight is presented, and on basis, technique for order preference by similarity to ideal solution (TOPSIS) method in Pythagorean fuzzy environment given. First, definition put forward, two examples are provided illustrate that can effectively prevent loss information. Second, notion real-value defined any real numbers, some basic operations, operation properties, sorting functions introduced. Finally, a Euclidean distance provided, new TOPSIS...

In this paper, we investigate the multi-criteria decision making(MCDM) problems with intuitionistic fuzzy information in which criteria are different priority levels. Based on degrees, introduce two kinds of aggregation operators: PRI-AND operators based degrees and PRI-OR degrees. Then also establish some important properties these their particular cases. Finally, develop a new method for addressing levels or An illustrative example is provided to prove effectiveness proposed approach.

In this paper, we present a priority degree method of hesitant fuzzy linguistic term sets (HFLTSs) based on type G function. First, obtain several invalid examples by using Rodríguez et al. and Lee al.'s HFLTSs. Considering these problems, second, after transforming HFLTS into the interval number proposing function, HFLTEs. Finally, compare both decision-making lee with our method. The result shows that is more rational.