Sustainable supplier selection (SSS) has become an essential task for decision-makers in competitive environments. We construct a new decision-making framework SSS. First, classical SSS usually includes fixed factors environmental, social and economic dimensions. Differently, we adopt from credit perspective with corporate system being promoted vigorously by the Chinese government. Next, employ...

The reaching of consensus in group decision-making (GDM) problems is a common task in group decision processes. In this contribution, we consider GDM with linguistic information. Different experts may have different levels of knowledge about a problem and, therefore, different linguistic term sets (multi-granular linguistic information) can be used to express their opinions. The aim of this pap...

Most information retrieval systems based on linguistic approaches use symmetrically and uniformly distributed linguistic term sets to express the weights of queries and the relevance degrees of documents. However, to improve the system-user interaction it seems more adequate to express these linguistic weights and degrees by means of unbalanced linguistic scales, i.e., linguistic term sets with...

Most tools and resources developed for natural language processing of Arabic are designed for Modern Standard Arabic (MSA) and perform terribly on Arabic dialects, such as Egyptian Arabic. Egyptian Arabic differs from MSA phonologically, morphologically and lexically and has no standardized orthography. We present a linguistically accurate, large-scale morphological analyzer for Egyptian Arabic...

In this paper, the authors propose an interval linguistic distribution model for multiple attribute decision making (MADM) problems with incomplete linguistic information, in which they use intervals as evaluators’ confidence levels indicating their belief degrees that a linguistic term fits an evaluation. By introducing the extent of ignoring information into this model, it can deal with incom...

The practice, common in fuzzy expert systems, to map linguistic data into fuzzy sets has some important reverse implications: given membership functions that represent different terms of a linguistic variable in one natural language , we can set out to search which of them best matches a given term in another language , on the basis of similarity assessments between individual terms. In other w...

Since the concept of linguistic variables was proposed, various kinds of linguistic terms have been used to express decision makers’ preference information in order to solve group decision making (GDM) problems. Probabilistic linguistic term set (PLTS) is a novel extension form of the existing linguistic variables. Based on it, the probabilistic linguistic preference relation (PLPR) has been pr...

Large-scale group decision-making (LS-GDM) problems are common in the daily life of human beings. Both information fusion and computing with words (CWW) technologies LS-GDM suffer from challenges. In current research, a proportional hesitant fuzzy linguistic term set (PHFLTS) will be applied to capture preferences sub-groups LS-GDM, which decreases lost processes. Novel semantic representation ...