An Integrated Maximizing Consistency and Multi-Choice Goal Programming Approach for Hybrid Multiple Criteria Group Decision Making Based on Interval-Valued Intuitionistic Fuzzy Number

Informatica ◽  
2015 ◽  
Vol 26 (4) ◽  
pp. 705-726 ◽  
Author(s):  
Xiaolu Zhang
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Goal Programming ◽  
Fuzzy Number ◽  
Group Decision ◽  
Multiple Criteria ◽  
Programming Approach ◽  
Intuitionistic Fuzzy Number ◽  
Intuitionistic Fuzzy ◽  
Interval Valued

scholarly journals Linguistic Interval-Valued Intuitionistic Fuzzy Copula Heronian Mean Operators for Multiattribute Group Decision-Making

2020 ◽  
Vol 2020 ◽  
pp. 1-25
Author(s):  
Lei Xu ◽  
Yi Liu ◽  
Haobin Liu
Keyword(s):  
Decision Making ◽  
Fuzzy Number ◽  
Group Decision ◽  
Decision Makers ◽  
Intuitionistic Fuzzy Number ◽  
Intuitionistic Fuzzy ◽  
Uncertainty Information ◽  
The Relationship ◽  
Interval Valued ◽  
Heronian Mean

As a generalization of the intuitionistic fuzzy number (IFN), the linguistic interval-valued intuitionistic fuzzy number (LIVIFN) is a flexible and superior tool to describe complex fuzzy uncertainty information. Heronian mean (HM) operator has the characteristic of considering the relationship between attributes. Extended copulas (ECs) and extended cocopulas (ECCs) are the promotion form of Archimedean t-norm and t-conorm (ATT). ECs and ECCs can generate versatile operational rules and can provide more choice for decision makers (DMs). Therefore, it is very necessary to take advantages of them. In this paper, ECs and ECCs, some specifics of ECs and ECCs, and score and accuracy functions of IVILFNs are gained first. Then, we propose the linguistic interval-valued intuitionistic fuzzy weighted copula Heronian mean (LIVIFWCHM) operator; also, some properties and five specific expressions of the LIVIFWCHM operator are discussed. Moreover, we also propose a new MAGDM approach based on the proposed LIVIFWCHM operator. Finally, a set of examples are used to demonstrate the effectiveness, generality, and flexibility of the proposed method.

DATA CONSTRUCTION PROCESS AND QUALIFLEX-BASED METHOD FOR MULTIPLE-CRITERIA GROUP DECISION MAKING WITH INTERVAL-VALUED INTUITIONISTIC FUZZY SETS

2013 ◽  
Vol 12 (03) ◽  
pp. 425-467 ◽  
Author(s):  
TING-YU CHEN
Keyword(s):  
Decision Making ◽  
Fuzzy Sets ◽  
Group Decision Making ◽  
Group Decision ◽  
Intuitionistic Fuzzy Sets ◽  
Multiple Criteria ◽  
Decision Makers ◽  
Intuitionistic Fuzzy ◽  
Uncertainty Indices ◽  
Interval Valued

Based on Jacquet-Lagreze's permutation method, QUALIFLEX is an outranking model that investigates all possible permutations of alternatives with respect to the consequences of all criteria. The purpose of this paper is to develop a QUALIFLEX-based method for multiple criteria group decision making within a decision environment of interval-valued intuitionistic fuzzy sets. We conduct a statistical inference approach with finite population correction to construct interval-valued intuitionistic fuzzy numbers. In addition, we incorporate the relative importance of decision makers and fuse individual opinions to form collective ratings using a modified method with weighted interval estimations. In view of diversiform preference types (weak order, strict order, difference order, interval bound, and ratio bound), we represent multiple decision makers' various forms of preference structures and assess criterion weights under incomplete information. By means of score functions, accuracy functions, membership-uncertainty indices, and hesitation-uncertainty indices, a ranking procedure is employed to identify a criterion-wise preference of alternatives. A QUALIFLEX-based model is then established to measure the level of concordance of the complete preference order for handling multiple criteria group decisions. The feasibility of the proposed method is illustrated by a practical problem relating to the selection of a landfill site. As indicated in the application, the proposed method is useful for handling complicated group decision-making problems that involve comprehensive criteria and limited alternatives.

scholarly journals Novel Multiple Attribute Group Decision-Making Methods Based on Linguistic Intuitionistic Fuzzy Information

Mathematics ◽  
2020 ◽  
Vol 8 (3) ◽  
pp. 322 ◽  
Author(s):  
Yuan Rong ◽  
Yi Liu ◽  
Zheng Pei
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Fuzzy Number ◽  
Group Decision ◽  
Intuitionistic Fuzzy Number ◽  
Fuzzy Information ◽  
Effective Technique ◽  
Intuitionistic Fuzzy ◽  
Multiple Attribute ◽  
Global Supplier

As an effective technique to qualitatively depict assessment information, a linguistic intuitionistic fuzzy number (LIFN) is more appropriate to portray vagueness and indeterminacy in actual situations than intuitionistic fuzzy number (IFN). The prominent feature of a Muirhead mean (MM) operator is that it has the powerful ability to capture the correlations between any input-data and MM operator covers other common operators by assigning the different parameter vectors. In the article, we first analyze the limitations of the existing ranking approaches of LIFN and propose a novel ranking approach to surmount these limitations. Secondly, we propound several novel MM operators to fuse linguistic intuitionistic fuzzy (LIF) information, such as the LIF Muirhead mean (LIFMM) operator, the weighted LIF Muirhead mean (WLIFMM) operator and their dual operators, the LIFDMM operator and the WLIFDMM operator. Subsequently, we discuss several desirable properties along with exceptional cases of them. Moreover, two novel multiple attribute group decision-making approaches are developed based upon these operators. Ultimately, the effectuality and practicability of the propounded methods are validated through dealing with a global supplier selection issue, and the comparative analysis and the merits of the presented approaches are demonstrated by comparing them with existing approaches.

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