Affiliations: [a] Oujiang College, Wenzhou University, Wenzhou, Zhejiang, China
| [b] School of Economics and Management, Xidian University, Xi’an, China
| [c] College Students Mental Health Education Service Center, Lanzhou Jiaotong University, Lanzhou, China
| [d]
Zhejiang University of Science and Technology, Hangzhou, Zhejiang, China
Correspondence:
[*]
Corresponding author. Bingzhen Sun and Xinrui Zhang, School of Economics and Management, Xidian University, Xi’an, 7100126 China. E-mails: bzsun@xidian.edu.cn and xin_rui97@163.com.
Note: [1] The Joint first author.
Abstract: Linguistic variable is an effective method of representation the preferences of a decision-maker for inaccuracy available information in decision making under uncertainty. This article investigates a multiple attribute ranking decision making problem with linguistic preference by using linguistic value soft rough set. Firstly, we present the definition of linguistic value fuzzy set by introducing the concept of linguistic variable into the original Zadeh’s fuzzy set. We then define the concept of linguistic value soft set and the pseudo linguistic value soft set over the alternative set and parameter set of discourse. Moreover, we investigate the basic operators and the mathematical properties of the linguistic value soft set. Subsequently, we establish the rough approximation of an uncertainty concept with linguistic value over the object set and parameter set, i.e., the linguistic value soft rough set model. Meanwhile, we discuss several deformations of the linguistic value soft rough lower and upper approximations as well as some fundamental properties of the linguistic value soft approximation operators. With reference on the exploring of the fundamental of linguistic value soft rough set, we construct a new method for handling with the multiple attribute ranking decision making problems with linguistic information by combining the proposed soft rough set and the VIKOR method. Then, we give the detailed decision procedure and steps for the established decision approach. At last, an extensive numerical example is further conducted to illustrate the process of the decision making principle and the results are satisfactory. The main contribution of this paper is twofold. One is to provide a new model of granular computing by infusion the soft set and rough set theory with linguistic valued information. Another is to try making a new way to handle multiple attribute decision making problems based on linguistic value soft rough set and the VIKOR method.
Keywords: Rough set, Soft set, Linguistic variable, Linguistic value soft
approximation space, VIKOR method
