A Novel Approach for Multiplicative Linguistic Group Decision Making Based on Symmetrical Linguistic Chi-Square Deviation and VIKOR Method

Most linguistic-based approaches to multi-attribute group decision making (MAGDM) use symmetric, uniformly distributed sets of additive linguistic terms to express the opinions of decision makers. However, in reality, there are also some problems that require the use of asymmetric, uneven, i.e., non-equilibrium, multiplicative linguistic term sets to express the evaluation. The purpose of this paper is to propose a new approach to MAGDM under multiplicative linguistic information. The aggregation of linguistic data is an important component in MAGDM. To solve this problem, we define a chi-square for measuring the difference between multiplicative linguistic term sets. Furthermore, the linguistic generalized weighted logarithm multiple averaging (LGWLMA) operator and linguistic generalized ordered weighted logarithm multiple averaging (LGOWLMA) operator are proposed based on chi-square deviation. On the basis of the proposed two operators, we develop a novel approach to GDM with multiplicative linguistic term sets. Finally, the evaluation of transport logistics enterprises is developed to illustrate the validity and practicality of the proposed approach.

Distance-based Knowledge measure of Hesitant Fuzzy Linguistic Term Set with its application in Multi-criteria decision-making

Motivated by the structural aspect of the probabilistic entropy, the concept of fuzzy entropy enabled the researchers to investigate the uncertainty due to vague information. Fuzzy entropy measures the ambiguity/vagueness entailed in a fuzzy set. Hesitant fuzzy entropy and hesitant fuzzy linguistic term set based entropy presents a more comprehensive evaluation of vague information. In the vague situations of multiple-criteria decision-making, entropy measure is utilized to compute the objective weights of attributes. The weights obtained due to entropy measures are not reasonable in all the situations. To model such situation, a knowledge measure is very significant, which is a structural dual to entropy. A fuzzy knowledge measure determines the level of precision in a fuzzy set. This article introduces the concept of a knowledge measure for hesitant fuzzy linguistic term sets (HFLTS) and show how it may be derived from HFLTS distance measures. Authors also investigate its application in determining the weights of criteria in multi-criteria decision-making (MCDM).

A Review: Language Awareness from the Perspective of Vocabulary Variation and Change

Language awareness refers to the consciousness of what language is and how language works. The process of establishing or developing language awareness should be a discovery of language use by learners themselves, maybe under the guidance of teachers. In this way, language awareness is considered not only as a linguistic term, but also a pedagogical approach. Just like society, change is also constant in the world of language. This paper aims to provide a reflection on language awareness from the angle of vocabulary variations and changes.

A two-sided gaming model for large-scale stable matching in sharing economy based on the probabilistic linguistic term sets

Sharing economy is significant for economic development, stable matching plays an essential role in sharing economy, but the large-scale sharing platform increases the difficulties of stable matching. We proposed a two-sided gaming model based on probabilistic linguistic term sets to address the problem. Firstly, in previous studies, the mutual assessment is used to obtain the preferences of individuals in large-scale matching, but the procedure is time-consuming. We use probabilistic linguistic term sets to present the preferences based on the historical data instead of time-consuming assessment. Then, to generate the satisfaction based on the preference, we regard the similarity between the expected preferences and actual preferences as the satisfaction. Considering the distribution features of probabilistic linguistic term sets, we design a shape-distance-based method to measure the similarity. After that, the previous studies aimed to maximize the total satisfaction in matching, but the individuals’ requirements are neglected, resulting in a weak matching result. We establish the two-sided gaming matching model from the perspectives of individuals based on the game theory. Meanwhile, we also study the competition from other platforms. Meanwhile, considering the importance of the high total satisfaction, we balance the total satisfaction and the personal requirements in the matching model. We also prove the solution of the matching model is the equilibrium solution. Finally, to verify the study, we use the experiment to illustrate the advantages of our study.

The application of probabilistic linguistic CODAS method based on new score function in multi-criteria decision-making

Probabilistic linguistic term sets (PLTSs) play an important role in multi-criteria decision-making(MCDM) problems because it can not only describe objects with several possible linguistic terms, but also represent the proportion of each linguistic term, which can effectively avoid the distortion of decision information to a greater extent and ensure the credibility of decision results. First, to compare PLTS more simply and reasonably, we define a new score function that takes into account partial deviations. Then considering the superiority of the classic combinative distance-based assessment (CODAS) method in the complete representation of information, it is extended to the probabilistic linguistic environment. Subsequently, we improved the classic CODAS method and proposed the PL-CODAS method. Finally, we apply the PL-CODAS method to a cases of venture investors choosing emerging companies, and we compare the proposed method with PL-TOPSIS method, PL-TODIM method and PL-MABAC method to verify its applicability and effectiveness.

Multi-attribute decision making method based on probabilistic linguistic term sets and its application in the evaluation of emergency logistics capacity

The occurrence of public health emergency will cause huge economic losses and casualties, which posed a huge threat to the economic and social development. In response to the emergency, a large amount of emergency relief supplies will be transported to the affected areas. Faced with this public health emergency of international concern, the concept of emergency logistics capacity and the evaluation model based on probabilistic linguistic term sets are proposed. In this paper, the emergency logistics capability evaluation is transformed into user demand evaluation, and the importance of each index of emergency logistics capability is determined by using Quality Function Deployment (QFD) and prospect theory. Under the probabilistic language information environment, a multi-attribute decision making method is established by using TODIM method. Finally, an example is given to verify the feasibility of the proposed method.