Abstract. The paper focuses its attention on solving Multi-objective intuitionistic fuzzy linear programming problem and Multi-objective intuitionistic fuzzy linear fractional programming problem by using weighting factor in which the constraints and the cost coefficients are intuitionistic fuzzy numbers. Weighting factor is used to convert problems that are multi-objective into single objectiv...

In this paper, a novel method for ranking of fuzzy numbers are proposed. In this method, decision maker is defined based on the center of mass at some cuts of a pair of fuzzy numbers in discreet version and center of mass on all of cuts of a pair of fuzzy numbers in continuous version. Our method can rank more than two fuzzy numbers simultaneously. Also, some properties of methods are described...

This paper processes a unification of Fuzzy TOPSIS and Data Envelopment Analysis DEA to select the units with most efficiency. This research is a two-stage model designed to fully rank the organizational alternatives, where each alternative has multiple inputs and outputs. First, the alternative evaluation problem is formulated byData Envelopment Analysis DEA and separately formulates each pair...

‎Ranking fuzzy numbers is generalization of the concepts of order, and class, and so have fundamental applications. Moreover, deriving the final efficiency and powerful ranking are helpful to decision makers when solving fuzzy problems. Selecting a good ranking method can apply to choosing a desired criterion in a fuzzy environment. There are numerous methods proposed for the ranking of fuzzy n...

Introduction/purpose: The paper discusses the selection of most optimal supplier using example an unmanned aircraft when decision maker has data a qualitative nature. Problems that arise in practice suppliers relate to adequate criteria as well way they are evaluated by maker. One ways assessing character is usage linguistic expressions, which gives makers freedom express their position and opi...

Ranking fuzzy numbers plays an important role in data analysis, decision making optimization, forecasting etc. The last few decades have seen a large number of methods investigated for ranking fuzzy numbers. In this paper, a new approach is proposed for the ranking of generalized trapezoidal fuzzy numbers namely Haar ranking and is based on the approximate coefficients and detailed coefficients...

This paper proposes an improved score function for the effective ranking order of interval-valued intuitionistic fuzzy sets (IVIFSs) and an interval-valued intuitionistic fuzzy TOPSIS method based on the score function to solve multicriteria decision-making problems in which all the preference information provided by decision-makers is expressed as interval-valued intuitionistic fuzzy decision ...

In recent years, there have been a growing interest in developing Multi-Criteria Decision Making (MCDM) and Group Decision Making (GDM) using type-2 fuzzy sets and Intuitionistic Fuzzy Sets (IFSs) which provide frameworks to handle the encountered uncertainties in decision making models. Previous research has shown the power of type-2 fuzzy logic systems to handle the linguistic uncertainties. ...

In this paper, we present a new method for ranking generalized fuzzy numbers for dealing with fuzzy risk analysis problems. The proposed method considers the defuzzified values, the heights and the spreads of generalized fuzzy numbers, simultaneously, for ranking generalized fuzzy numbers. It gets better ranking results to rank generalized fuzzy numbers than the existing methods. We also apply ...