TODIM Method for Single-Valued Neutrosophic Multiple Attribute Decision Making

Dong-Sheng Xu,Gui-Wu Wei,Cun Wei

doi:10.3390/info8040125

Abstract

Recently, the TODIM has been used to solve multiple attribute decision making (MADM) problems. The single-valued neutrosophic sets (SVNSs) are useful tools to depict the uncertainty of the MADM. In this paper, we will extend the TODIM method to the MADM with the single-valued neutrosophic numbers (SVNNs). Firstly, the definition, comparison, and distance of SVNNs are briefly presented, and the steps of the classical TODIM method for MADM problems are introduced. Then, the extended classical TODIM method is proposed to deal with MADM problems with the SVNNs, and its significant characteristic is that it can fully consider the decision makers’ bounded rationality which is a real action in decision making. Furthermore, we extend the proposed model to interval neutrosophic sets (INSs). Finally, a numerical example is proposed.

Highlights

Multiple attribute decision making (MADM) is a hot research area of the decision theory domain, which has had wide applications in many fields, and attracted increasing attention [1,2]
We extend the proposed model to interval neutrosophic sets (INSs)
Due to the fuzziness and uncertainty of the alternatives in different attributes, attribute values in decision making problems are not always represented as real numbers, and they can be described as fuzzy numbers in more suitable occasions, such as interval-valued numbers [3,4], triangular fuzzy variables [5,6,7,8], linguistic variables [9,10,11,12,13] or uncertain linguistic variables [14,15,16,17,18,19,20,21], intuitionistic fuzzy numbers (IFSs) [22,23,24,25,26,27] or interval-valued intuitionistic fuzzy numbers (IVIFSs) [28,29,30,31], and single-valued neutrosophic sets (SVNSs) [32] or

Summary

Introduction

Multiple attribute decision making (MADM) is a hot research area of the decision theory domain, which has had wide applications in many fields, and attracted increasing attention [1,2]. Since Fuzzy set (FS), which is a very useful tool to process fuzzy information, was firstly proposed by Zadeh [34], it has been regarded as an useful tool to solve MADM [35,36], fuzzy logic [37], and patterns recognition [38]. The concepts of a SVNS [32] and an INS [33]

Objectives

Methods

Conclusion