In this paper, an extended ranking method for fuzzy numbers, which is a synthesis of fuzzy targets and the Dempster–Shafer Theory (DST) of evidence, is devised. The use of fuzzy targets to reflect human viewpoints in fuzzy ranking is not new. However, different fuzzy targets can lead to contradictory fuzzy ranking results; making it difficult to reach a final decision. In this paper, the result...

the importance as well as the difficulty of the problem of ranking fuzzy numbers is pointed out. here we consider approaches to the ranking of fuzzy numbers based upon the idea of associating with a fuzzy number a scalar value, its signal/noise ratios, where the signal and the noise are defined as the middle-point and the spread of each $gamma$-cut of a fuzzy number, respectively. we use the va...

Ranking of fuzzy sets plays an important role in decision making, optimization, forecasting, etc. Fuzzy sets must be ranked before an action is taken by a decision maker. Fuzzy sets with different heights are a generalization of the ordinary fuzzy sets. In this paper, with the help of several counterexamples, it is proved that the ranking method proposed by Lee and Chen (Expert Systems with App...

A multi criteria decision making in ranking the bus companies using fuzzy rule is proposed. The proposed method uses the application of fuzzy sets and approximate reasoning in deciding the ranking of the performance of several bus companies. The proposed method introduces data normalization using similarity function which dampens extreme values that exist in the data. The use of the model is su...

The main aim of this paper is to present a novel method for ranking hesitant fuzzy sets (HFSs) based on transforming HFSs into fuzzy sets (FSs). The idea behind the method is an interesting HFS decomposition which is referred here to as the horizontal representation in the current study. To show the validity of the proposed ranking method, we apply it to solve a multi-attribute decision-making ...

Ranking of fuzzy numbers play an important role in decision making, optimization, forecasting etc. Fuzzy numbers must be ranked before an action is taken by a decision maker. In this paper, with the help of several counter examples it is proved that ranking method proposed by Chen and Chen (Expert Syst Appl 36:6833–6842, 2009) is incorrect. The main aim of this paper is to propose a new approac...

-This study presents an approximate approach for ranking fuzzy numbers based on the left and right dominance. The proposed approach only requires a few left and right spreads at some a-levels of fuzzy numbers to determine the respective dominance of one fuzzy number over the other. The total dominance is then determined by combining the left and right dominance based on a decision maker's optim...

Fuzzy numbers can be introduced in order to model imprecise situations involving real numbers, and one of the first problem one meets working with these is to decide what type of order to use on the fuzzy number set. In fact this set does not have a natural total ranking. Different methods for ranking fuzzy numbers has been described. Most of these are defined by a function which maps each fuzz...

This paper presents an area-based approach to ranking fuzzy numbers in fuzzy decision making. To ensure that all the information that a fuzzy number has is adequately considered, the concepts of the absolute area and the degree of deviation of a fuzzy number are integrated into the process of comparing and ranking fuzzy numbers. To help the decision maker better address the risk inherent in the...