Trapezoidal neutrosophic set and its application to multiple attribute decision-making

Based on the combination of trapezoidal fuzzy numbers and a single-valued neutrosophic set, this paper proposes a trapezoidal neutrosophic set, some operational rules, score and accuracy functions for trapezoidal neutrosophic numbers

A review of fuzzy AHP methods for decision-making with subjective judgements

Analytic Hierarchy Process (AHP) is a broadly applied multi-criteria decision-making method to determine the weights of criteria and priorities of alternatives in a structured manner based on pairwise comparison. As subjective judgments during comparison might be imprecise, fuzzy sets have been combined with AHP. This is referred to as fuzzy AHP or FAHP. An increasing amount of papers are published which describe different ways to derive the weights/priorities from a fuzzy comparison matrix, but seldomly set out the relative benefits of each approach so that the choice of the approach seems arbitrary. A review of various fuzzy AHP techniques is required to guide both academic and industrial experts to choose suitable techniques for a specific practical context. This paper reviews the literature published since 2008 where fuzzy AHP is applied to decision-making problems in industry, particularly the various selection problems. The techniques are categorised by the four aspects of developing a fuzzy AHP model: (i) representation of the relative importance for pairwise comparison, (ii) aggregation of fuzzy sets for group decisions and weights/priorities, (iii) defuzzification of a fuzzy set to a crisp value for final comparison, and (iv) consistency measurement of the judgements. These techniques are discussed in terms of their underlying principles, origins, strengths and weakness. Summary tables and specification charts are provided to guide the selection of suitable techniques. Tips for building a fuzzy AHP model are also included and six open questions are posed for future work

Triangular Cubic Hesitant Fuzzy Einstein Hybrid Weighted Averaging Operator and Its Application to Decision Making

In this paper, triangular cubic hesitant fuzzy Einstein weighted averaging (TCHFEWA) operator, triangular cubic hesitant fuzzy Einstein ordered weighted averaging (TCHFEOWA) operator and triangular cubic hesitant fuzzy Einstein hybrid weighted averaging (TCHFEHWA) operator are proposed. An approach to multiple attribute group decision making with linguistic information is developed based on the TCHFEWA and the TCHFEHWA operators. Furthermore, we establish various properties of these operators and derive the relationship between the proposed operators and the existing aggregation operators. Finally, a numerical example is provided to demonstrate the application of the established approach

Density aggregation operators based on the intuitionistic trapezoidal fuzzy numbers for multiple attribute decision making

With respect to the multiple attribute decision making problems in which the attribute values take the form of the intuitionistic trapezoidal fuzzy numbers, some methods based on density aggregation operators are proposed. Firstly, the definition, expected value and the ranking method of intuitionistic trapezoidal fuzzy numbers are introduced, and the method of calculating density weighted vector is proposed. Then some density aggregation operators based on interval numbers and intuitionistic trapezoidal fuzzy numbers are developed, and a multiple attribute decision making method is presented. Finally an illustrative example is given to verify the developed approach and to demonstrate its practicality and effectiveness

A SD-IITFOWA operator and TOPSIS based approach for MAGDM problems with intuitionistic trapezoidal fuzzy numbers

The aim of this article is to investigate an approach to multiple attribute group decision making (MAGDM) problems in which the information about decision makers (DMs) weights is completely unknown in advance, the attributes are inter-dependent, and the attribute values take the form of intuitionistic trapezoidal fuzzy numbers. First, the concept of similarity degree (SD) for two intuitionistic trapezoidal fuzzy decision matrixes is defined, which measures the level of consensus between individual decision opinion and group decision opinion. Next, we develop some IITFOWA operators to aggregate intuitionistic trapezoidal fuzzy decision matrixes in MAGDM problems. In particular, we present the SD induced IITFOWA (SD-IITFOWA) operator, which induces the order of argument values by utilizing the similarity degree of decision makers. This operator aggregates individual opinion in such a way that more importance is placed on the most similarity one. Then, a SD-IITFOWA operator and TOPSIS method based approach is developed to solve the MAGDM problems with intuitionistic trapezoidal fuzzy numbers. Finally, the developed approach is used to select the right suppliers for a computer company

Multi-criteria decision-making method based on intuitionistic trapezoidal fuzzy prioritised owa operator

In the real decision-making, there are many multiple attribute decision-making (MADM) problems, in which there exists the prioritised relationship among decision-making attributes. In this paper, with respect to the prioritised multi-criteria decision-making problems under intuitionistic trapezoidal fuzzy information, a new decision-making method on the basis of the intuitionistic trapezoidal fuzzy prioritised ordered weighted aggregation operator has been proposed. Firstly, the definitions, operational rules and characteristics of intuitionistic trapezoidal fuzzy numbers and POWA operator have been introduced. Then, intuitionistic trapezoidal fuzzy prioritised ordered weighted aggregation (ITFPOWA) operator has been defined as well as the computational method of associated weight, and some properties have been studied and proved. Furthermore, based on the ITFPOWA operator, an approach to the multi-criteria decision-making with intuitionistic trapezoidal fuzzy numbers has been established. Finally, an illustrative example has been given to prove the evaluation procedures of the developed approach and to demonstrate its practicality and validity