Search

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. [ABSTRACT FROM AUTHOR]

Companies are attaching more and more importance to sustainable supply chain management (SSCM) as which makes the right strategy measures for companies. Due to the complexity of external environmental factors and internal structure, sustainable supply chain management is vulnerable to various risks. The purpose of this paper is to present a new two-stage approach for determining the best practitioner in Iran Pars Special Economic Energy Zone based on the sustainable supply chain risk management (SSCRM). The best and worst method (BWM) is used to determine the weight of risk factors. Then the method of linguistic value soft set is used to assess the impact of risk factors on each company's sustainable supply chain which is a multiple attribute decision making problem with language preference in the second stage. Consequently, the ranking results of sustainable supply chain of each enterprise are obtained. This study contributes to finding the key risk factors of SSCRM. Evaluating these companies SSCRM with preference information, the best practitioner can obtain. The combination of BWM and linguistic value soft set approach provides a new nonparametric theoretical method and tool for this kind of decision-making problems with this background. At the same time, the conclusions of this study have guiding significance for the implementation of industrial supply chain. Limitations of the study along with future research directions are also presented. [ABSTRACT FROM AUTHOR]