Multiple Attributes Group Decision-Making under Interval-Valued Dual Hesitant Fuzzy Unbalanced Linguistic Environment with Prioritized Attributes and Unknown Decision-Makers’ Weights

Abstract

Aiming at a special type of ill-defined complicate multiple attributes group decision-making (MAGDM) problem, which exhibits hybrid complexity features of decision hesitancy, prioritized evaluative attributes, and unknown decision-makers' weights, we investigate an effective approach in this paper. To accommodate decision hesitancy, we employ a compound expression tool of interval-valued dual hesitant fuzzy unbalanced linguistic set (IVDHFUBLS) to help decision-makers elicit their assessments more comprehensively and completely. To exploit prioritization relations among evaluating attributes, we develop a prioritized weighted aggregation operator for IVDHFUBLS-based decision-making scenarios and then analyze its properties and special cases. To objectively derive unknown decision-makers' weighting vector, we next develop a hybrid model that simultaneously takes into account the overall accuracy measure of the individual decision matrix and maximizing deviation among all decision matrices. Furthermore, on the strength of the above methods, we construct an MAGDM approach and demonstrate its practicality and effectiveness using applied study on a green supplier selection problem.

Probabilistic Hybrid Linguistic Approaches for Multiple Attribute Group Decision Making with Decision Hesitancy and the Prioritization of Attribute Relationships

“…Step II-6. Obtain overall group aggregation results r j ( j = 1, 2, 3, 4) by Equation (36). Please note that details about r j ( j = 1, 2, 3, 4) are omitted here for brevity.…”

“…However, when it comes to more complicated MAGDM problems, where problem structures are ill-defined for fuzzy quantification, Zadeh [25] has advocated the usage of linguistic variables for decision makers to qualitatively express their uncertain preferences. To this end, because of the merit in eliciting decision maker assessments more directly and precisely, linguistic variables have been continuously extended to accommodate various scenarios, such as unbalanced linguistic variables [26][27][28][29], uncertain linguistic variables [30][31][32][33], intuitionistic uncertain variables [34,35], hesitant fuzzy uncertain linguistic variables [15], and hesitant fuzzy unbalanced linguistic variables [36], among others. Although the above extensions of linguistic variables are very effective in situations where decision makers can approximate the most precise linguistic label in accordance with their assessment, Rodríguez et al [37] revealed that decision makers are often cognitively irresolute among several possible linguistic labels.…”

Multiple-Criteria Decision-Making (MCDM) Techniques for Business Processes Information Management

“…A compound expression tool of interval-valued dual hesitant fuzzy unbalanced linguistic set (IVDHFUBLS) is proposed to help decision-makers by elucidating their assessments more comprehensively and completely. It also prioritizes weighted aggregation operator for IVDHFUBLS-based decision-making scenarios and then analyzes its properties and special cases [26]. A novel convex combination of multi-hesitant fuzzy numbers (MHFNs) is introduced along with some aggregation operators and their corresponding properties are discussed in detail [27].…”

A Supplier Selection Decision-Making Approach for Complex Product Development Based on Hesitant Fuzzy Information

“…As a consequence, multiple-attribute decision-making problems [47,48] with hesitant fuzzy information have also paid attention to the process of socio-economic management. Nevertheless, the determination of attribute weights which affects the decision-making process is a significant influence factor [49][50][51], which plays an important role in scientific and reasonable decision-making. To dig into this problem deeply, for instance, Wang [52] investigated a weighting method based on the entropy principle.…”