scholarly journals An Approach to Linguistic Multiple Attribute Decision-Making Based on Unbalanced Linguistic Generalized Heronian Mean Aggregation Operator

2018 ◽  
Vol 2018 ◽  
pp. 1-25 ◽  
Author(s):  
Bing Han ◽  
Huayou Chen ◽  
Jiaming Zhu ◽  
Jinpei Liu
Keyword(s):  
Decision Making ◽  
Multiple Attribute Decision Making ◽  
Aggregation Operators ◽  
Low Carbon ◽  
Weighted Arithmetic ◽  
Multiple Attribute ◽  
Linguistic Assessment ◽  
Linguistic Assessment Information ◽  
Heronian Mean ◽  
Generalized Arithmetic

This paper proposes an approach to linguistic multiple attribute decision-making problems with interactive unbalanced linguistic assessment information by unbalanced linguistic generalized Heronian mean aggregation operators. First, some generalized Heronian mean aggregation operators with unbalanced linguistic information are proposed, involving the unbalanced linguistic generalized arithmetic Heronian mean operator and the unbalanced linguistic generalized geometric Heronian mean operator. For the situation that the input arguments have different degrees of importance, the unbalanced linguistic generalized weighted arithmetic Heronian mean operator and the unbalanced linguistic generalized weighted geometric Heronian mean operator are developed. Then we investigate their properties and some particular cases. Finally, the effectiveness and universality of the developed approach are illustrated by a low-carbon tourist instance and comparison analysis. A sensitivity analysis is performed as well to test the robustness of proposed methods.

scholarly journals Multiple Attribute Decision-Making Method Using Linguistic Cubic Hesitant Variables

Algorithms ◽  
2018 ◽  
Vol 11 (9) ◽  
pp. 135 ◽  
Author(s):  
Jun Ye ◽  
Wenhua Cui
Keyword(s):  
Decision Making ◽  
Score Function ◽  
Multiple Attribute Decision Making ◽  
Aggregation Operators ◽  
Hesitant Fuzzy Set ◽  
Least Common Multiple ◽  
Weighted Arithmetic ◽  
Multiple Attribute ◽  
Multi Attribute Decision Making ◽  
Human Thinking

Linguistic decision making (DM) is an important research topic in DM theory and methods since using linguistic terms for the assessment of the objective world is very fitting for human thinking and expressing habits. However, there is both uncertainty and hesitancy in linguistic arguments in human thinking and judgments of an evaluated object. Nonetheless, the hybrid information regarding both uncertain linguistic arguments and hesitant linguistic arguments cannot be expressed through the various existing linguistic concepts. To reasonably express it, this study presents a linguistic cubic hesitant variable (LCHV) based on the concepts of a linguistic cubic variable and a hesitant fuzzy set, its operational relations, and its linguistic score function for ranking LCHVs. Then, the objective extension method based on the least common multiple number/cardinality for LCHVs and the weighted aggregation operators of LCHVs are proposed to reasonably aggregate LCHV information because existing aggregation operators cannot aggregate LCHVs in which the number of their hesitant components may imply difference. Next, a multi-attribute decision-making (MADM) approach is proposed based on the weighted arithmetic averaging (WAA) and weighted geometric averaging (WGA) operators of LCHVs. Lastly, an illustrative example is provided to indicate the applicability of the proposed approaches.

scholarly journals An Algorithm for Fuzzy Negations Based-Intuitionistic Fuzzy Copula Aggregation Operators in Multiple Attribute Decision Making

Algorithms ◽  
2020 ◽  
Vol 13 (6) ◽  
pp. 154
Author(s):  
Stylianos Giakoumakis ◽  
Basil Papadopoulos
Keyword(s):  
Decision Making ◽  
Multiple Attribute Decision Making ◽  
Aggregation Operators ◽  
Archimedean Copulas ◽  
Computation Model ◽  
Intuitionistic Fuzzy ◽  
Weighted Arithmetic ◽  
Multiple Attribute ◽  
Published Paper

In this paper, we develop a novel computation model of Intuitionistic Fuzzy Values with the usage of fuzzy negations and Archimedean copulas. This novel computation model’s structure is based on the extension of the existing operations of intuitionistic fuzzy values with some classes of fuzzy negations. Many properties of the proposed operations are investigated and proved. Additionally, in this paper we introduce the concepts of intuitionistic fuzzy Archimedean copula weighted arithmetic and geometric aggregation operators based on fuzzy negations, including a further analysis of their properties. Finally, using a case study from an already published paper we found that our method has many advantages.

Density aggregation operators for interval-valued q-rung orthopair fuzzy numbers and their application in multiple attribute decision making

2021 ◽  
pp. 1-14
Author(s):  
Huijuan Guo ◽  
Ruipu Yao
Keyword(s):  
Decision Making ◽  
Fuzzy Numbers ◽  
Multiple Attribute Decision Making ◽  
Aggregation Operator ◽  
Aggregation Operators ◽  
Weighted Arithmetic ◽  
Geometric Average ◽  
Novel Approach ◽  
Multiple Attribute ◽  
Interval Valued

The symmetry between fuzzy evaluations and crisp numbers provides an effective solution to multiple attribute decision making (MADM) problems under fuzzy environments. Considering the effect of information distribution on decision making, a novel approach to MADM problems under the interval-valued q-rung orthopair fuzzy (Iq-ROF) environments is put forward. Firstly, the clustering method of interval-valued q-rung orthopair fuzzy numbers (Iq-ROFNs) is defined. Secondly, Iq-ROF density weighted arithmetic (Iq-ROFDWA) intermediate operator and Iq-ROF density weighted geometric average (Iq-ROFDWGA) intermediate operator are developed based on the density weighted intermediate operators for crisp numbers. Thirdly, combining the density weighted intermediate operators with the Iq-ROF weighted aggregation operators, Iq-ROF density aggregation operators including Iq-ROF density weighted arithmetic (Iq-ROFDWAA) aggregation operator and Iq-ROF density weighted geometric (Iq-ROFDWGG) aggregation operator are proposed. Finally, effectiveness of the proposed method is verified through a numerical example.

scholarly journals Multiple Attribute Decision-Making Based on Three-Parameter Generalized Weighted Heronian Mean

Mathematics ◽  
2021 ◽  
Vol 9 (12) ◽  
pp. 1363
Author(s):  
Ximei Hu ◽  
Shuxia Yang ◽  
Ya-Ru Zhu
Keyword(s):  
Decision Making ◽  
Multiple Attribute Decision Making ◽  
Correlation Factor ◽  
Aggregation Operators ◽  
Practical Significance ◽  
Correlation Relationship ◽  
Multiple Attribute ◽  
Aggregation Problem ◽  
The Relationship ◽  
Heronian Mean

For the aggregation problem of attributes with a correlation relationship, it is often necessary to take the correlation factor into account in order to make the decision results more objective and reasonable. The Heronian mean is an aggregation operator which reflects the interaction between attributes. It is of great theoretical and practical significance to study and popularize the multiple attribute decision-making methods based on the Heronian mean operator. In this paper, we first give a new three-parameter generalized weighted Heronian mean (TPGWHM), which has a series of excellent properties such as idempotency, monotonicity and boundedness. At the same time, the relationship between the TPGWHM and the existing aggregation operators is given. Then, we propose the intuitionistic fuzzy three-parameter generalized weighted Heronian mean (IFTPGWHM) and give its idempotency, monotonicity, boundedness and limit properties. On this basis, a multiple attribute decision-making method based on the TPGWHM and a multiple attribute decision-making method based on the IFTPGWHM are given, and corresponding examples are given and analyzed.

Applied-Information Technology and Data Processing in Determination of Subjective Weights in Multiple Attribute Decision Making

2014 ◽  
Vol 662 ◽  
pp. 271-276
Author(s):  
Bian Ping Su ◽  
Hong Yan Su
Keyword(s):  
Decision Making ◽  
Information Technology ◽  
Subjective Evaluation ◽  
Multiple Attribute Decision Making ◽  
Multiple Attribute ◽  
Multi Attribute Decision Making ◽  
Linguistic Assessment ◽  
Index Weight ◽  
Linguistic Assessment Information

The index weight plays a very important role and directly affects the decisions of the results in the multi-attribute decision making, this paper applys information technology and date processing to determine subjective weights in multiple attribute decision making ,and combinate tuple Linguistic and AHP to solve the subjective indicators with linguistic assessment information right weight information.Finally,obtained subjective evaluation index weights and an example is given to approve the effectiveness and feasibility of the method.

scholarly journals Heronian Mean Operator of Linguistic Neutrosophic Cubic Numbers and Their Multiple Attribute Decision-Making Methods

2018 ◽  
Vol 2018 ◽  
pp. 1-13 ◽  
Author(s):  
Changxing Fan ◽  
Jun Ye
Keyword(s):  
Decision Making ◽  
Information Aggregation ◽  
Multiple Attribute Decision Making ◽  
Aggregation Operator ◽  
Aggregation Operators ◽  
Multiple Attribute ◽  
Decision Methods ◽  
Multiattribute Decisions ◽  
Heronian Mean

Many aggregation operators in multiattribute decisions assume that attributes are independent of each other; this leads to an unreasonable situation in information aggregation and decision-making. Heronian mean is the aggregation operator that can embody the interaction between attributes. In this paper, we merge the linguistic neutrosophic cubic number (LNCN) and the Heronian mean operator together to develop a LNCN generalized weighted Heronian mean (LNCNGWHM) operator and a LNCN three-parameter weighted Heronian mean (LNCNTPWHM) operator and then discuss their properties. Further, two multiattribute decision methods based on the proposed LNCNGWHM or LNCNTPWHM operator are introduced under LNCN environment. Finally, an example is used to indicate the effectiveness of the developed methods.

SOME HARMONIC AGGREGATION OPERATORS WITH 2-TUPLE LINGUISTIC ASSESSMENT INFORMATION AND THEIR APPLICATION TO MULTIPLE ATTRIBUTE GROUP DECISION MAKING

2011 ◽  
Vol 19 (06) ◽  
pp. 977-998 ◽  
Author(s):  
G. W. WEI
Keyword(s):  
Decision Making ◽  
Decision Analysis ◽  
Group Decision Making ◽  
Group Decision ◽  
Aggregation Operators ◽  
Linguistic Information ◽  
Multiple Attribute ◽  
Linguistic Assessment ◽  
Linguistic Assessment Information ◽  
Selection Of

With respect to multiple attribute group decision making problems with linguistic information of attribute values, a group decision analysis is proposed. Some new aggregation operators are proposed: the 2-tuple linguistic weighted harmonic averaging (TWHA), 2-tuple linguistic ordered weighted harmonic averaging (TOWHA) and 2-tuple linguistic combined weighted harmonic averaging (TCWHA) operator and properties of the operators are analyzed. Then, a method based on the TWHA and TCWHA operators for multiple attribute group decision making is presented. In this approach, alternative appraisal values are calculated by the aggregation of 2-tuple linguistic information. Thus, the ranking of alternative or selection of the most desirable alternative(s) is obtained by the comparison of 2-tuple linguistic information. Finally, a numerical example is used to illustrate the applicability and effectiveness of the proposed method.

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