ABSTRACT
In consideration of the different importance degrees that may be assigned to all possible linguistic terms, this paper investigates a novel three-way group decision-making method based on the probabilistic linguistic term set (PLTS) information systems. We first construct PLTS information systems based on multiple attributes. Considering the reliabilities of the experts, we determine the weights of the experts by the similarities of the information provided by the expert with regard to other experts. Subsequently, using the evidential reasoning (ER) method, we aggregate the information provided by all experts and obtain the conditional probability of each object. The introduction of the ER rules and the weights of experts successfully solve the problem of conflict between the evaluation information. Then an approach is presented to calculate loss functions and thresholds, which reduces the subjectivity of the decision-making process. Next, the decision result of each object is deduced based on the minimum-loss principle. Finally, a case study about the selection of mask foundries during the COVID-19 is used to demonstrate the effectiveness of our proposed method. And the superiority of our proposed method are proved by comparative analysis. © 2023, The Author(s) under exclusive licence to Taiwan Fuzzy Systems Association.
ABSTRACT
This study examines decision theory based on interval type-2 fuzzy sets with linguistic information for the three-way decision approach by addressing the challenge of uncertainty for information analysis and fusion in subjective decision-making processes. First, the interval type-2 fuzzy linguistic term sets (IT2 FLTSs) are defined to represent and normalize the uncertain preference information in linguistic decision-making. Subsequently, perception computing based on computing with words paradigm is introduced to implement information fusion among different decision-makers in the linguistic information-based fuzzy logic reasoning process. Then, a three-way decision (3WD) theory based on IT2 FLTSs with fuzzy neighborhood covering is proposed, and the corresponded tri-partitioning strategies that satisfy Jaccard similarity of membership distributions are given. Finally, 3WD theory is applied to multi-criteria group decision-making with linguistic terms, and the algorithm steps are illustrated by a promising application under the background of coronavirus disease 2019 to reveal the feasibility and practicability of the proposed approach. © 2022 - IOS Press. All rights reserved.
ABSTRACT
In Quality function deployment (QFD) approach, customers tend to express their needs in linguistic terms rather than exact numerical values and these needs generally contain vague and imprecise information. To overcome this challenge and to use the method more effectively for complex customer-oriented design problems, this paper introduces a novel intuitionistic Z-fuzzy QFD method based on Chebyshev's inequality (CI) and applies it for a new product design. CI provides the assignment of a more objective reliability function. The reliability value is based on the maximum probability obtained from CI. Then, the expected values of lower and upper bounds of interval-valued intuitionistic fuzzy (IVIF) numbers are determined. A competitive analysis among our firm and competitor firms and an integrative analysis for the different functions of QFD is presented. The proposed Z-fuzzy QFD method is applied to the design and development of a hand sanitizer for struggling with COVID-19. © 2022 Vilnius University.
ABSTRACT
Fuzzy hybrid models are strong mathematical tools to address vague and uncertain information in real-life circumstances. The aim of this article is to introduce a new fuzzy hybrid model named as of q-rung orthopair m-polar fuzzy soft set (q-RO-m-PFSS) as a robust fusion of soft set (SS), m-polar fuzzy set (m-PFS) and q-rung orthopair fuzzy set (q-ROFS). A q-RO-m-PFSS is a new approach towards modelling uncertainties in the multi-criteria decision making (MCDM) problems. Some fundamental operations on q-RO-m-PFSSs, their key properties, and related significant results are introduced. Additionally, the complexity of logistics and supply chain management during COVID-19 is analysed using TOPSIS (technique for ordering preference through the ideal solution) and GRA (grey relational analysis) with the help of q-RO-m-PFS information. The linguistic terms are used to express q-RO-m-PFS information in terms of numeric values. The proposed approaches are worthy efficient in the selection of ventilator's manufacturers for the patients suffering from epidemic disease named as COVID-19. A practical application of proposed MCDM techniques is demonstrated by respective numerical examples. The comparison analysis of the final ranking computed by proposed techniques is also given to justify the feasibility, applicability and reliability of these techniques.