scholarly journals Prioritized Aggregation Operators and Correlated Aggregation Operators for Hesitant 2-Tuple Linguistic Variables

Symmetry ◽  
2018 ◽  
Vol 10 (2) ◽  
pp. 39 ◽  
Author(s):  
Lidong Wang ◽  
Yanjun Wang ◽  
Xiaodong Liu
Keyword(s):  
Aggregation Operators ◽  
Linguistic Variables ◽  
Prioritized Aggregation Operators

scholarly journals Multigranular Uncertain Linguistic Prioritized Aggregation Operators and Their Application to Multiple Criteria Group Decision Making

2013 ◽  
Vol 2013 ◽  
pp. 1-13 ◽  
Author(s):  
Ding-Hong Peng ◽  
Tie-Dan Wang ◽  
Chang-Yuan Gao ◽  
Hua Wang
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Weighted Average ◽  
Aggregation Operators ◽  
Multiple Criteria ◽  
Linguistic Variables ◽  
Prioritized Aggregation Operator ◽  
Prioritized Aggregation Operators ◽  
Decision Elements

We investigate multiple criteria group decision-making problems in which there are priority relationships between the decision elements (criteria and experts), and decision information provided by decision makers takes the form of multigranular uncertain linguistic information. Firstly, some operational laws and possibility degree of multi-granular uncertain linguistic variables are introduced. Then, some new linguistic aggregation operators based on the prioritized aggregation operator, such as the multigranular uncertain linguistic prioritized weighted average (MULPWA) operator and the multigranular uncertain linguistic prioritized ordered weighted average (MULPOWA) operator, are developed and their desirable properties are studied. The prominent characteristics of these proposed operators are that they can aggregate directly the uncertain linguistic variables whose values form the linguistic term sets with different granularities and convey the prioritization phenomenon among the aggregated arguments. Furthermore, based on the MULPWA and MULPOWA operators, an approach to deal with multiple criteria group decision-making problems under multi-granular uncertain linguistic environments is developed. Finally, a practical example is provided to illustrate the multiple criteria group decision-making process.

Multiple Attribute Decision-Making Methods with Unbalanced Linguistic Variables Based on Maclaurin Symmetric Mean Operators

2019 ◽  
Vol 18 (01) ◽  
pp. 105-146 ◽  
Author(s):  
Fei Teng ◽  
Peide Liu ◽  
Li Zhang ◽  
Juan Zhao
Keyword(s):  
Decision Making ◽  
Multiple Attribute Decision Making ◽  
Aggregation Operators ◽  
Linguistic Variables ◽  
Numerical Example ◽  
Maclaurin Symmetric Mean ◽  
Multiple Attribute ◽  
Linguistic Term

In this paper, we firstly introduced the unbalanced linguistic term sets, the linguistic transforming methodology, the Maclaurin symmetric mean (MSM) operator and dual MSM (DMSM) operator. Then, we proposed the closed operational rules of unbalanced linguistic variables, and several new MSM aggregation operators, including unbalanced linguistic MSM (ULMSM) operator, weighted unbalanced linguistic MSM (WULMSM) operator, unbalanced linguistic DMSM (ULDMSM) operator and weighted unbalanced linguistic DMSM (WULDMSM) operator. Further, we proposed two multiple attribute decision-making (MADM) methods under unbalanced linguistic environments based on the WULMSM operator and WULDMSM operator, respectively. Finally, a numerical example is used to show the applicability and effectiveness of the proposed MADM methods and to reveal their advantages by comparing with the existing methods.

scholarly journals Bonferroni Prioritized Aggregation Operators Applied to Government Transparency

Mathematics ◽  
2020 ◽  
Vol 9 (1) ◽  
pp. 24 ◽  
Author(s):  
Luis A. Perez-Arellano ◽  
Fabio Blanco-Mesa ◽  
Ernesto Leon-Castro ◽  
Victor Alfaro-Garcia
Keyword(s):  
Main Idea ◽  
Weighted Average ◽  
Aggregation Operator ◽  
Aggregation Operators ◽  
Decision Makers ◽  
Bonferroni Mean ◽  
Different Types ◽  
Ordered Weighted Average ◽  
Types Of Information ◽  
Prioritized Aggregation Operators

This article applies the Bonferroni prioritized induced heavy ordered weighted average (OWA) to analyze a series of data and focuses on the Bonferroni average and heavy induced prioritized aggregation operators. The objective of the present work is to present a new aggregation operator that combines the heavy induced prioritized Bonferroni and its formulations and represents the Bonferroni mean with variables that induce an order with vectors that are greater than one. This work develops some extensions using prioritization. The main advantage is that different types of information provided by a group of decision makers to compare real situations are included in this formulation. Finally, an example using the operators to calculate the transparency of the websites of the 32 states of Mexico was performed. The main idea was to visualize how the ranking can change depending on the importance of the five components of the methodology. The main results show that it is possible to detect some important changes depending on the operator and the experts considered.

scholarly journals THE MULTI-ATTRIBUTE GROUP DECISION MAKING METHOD BASED ON THE INTERVAL GREY LINGUISTIC VARIABLES WEIGHTED HARMONIC AGGREGATION OPERATORS

2013 ◽  
Vol 19 (3) ◽  
pp. 409-430 ◽  
Author(s):  
Fang Jin ◽  
Peide Liu ◽  
Xin Zhang
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Aggregation Operators ◽  
Computational Results ◽  
Linguistic Variables ◽  
Operation Rules ◽  
Operator Interval ◽  
Multiple Attribute ◽  
Novel Method

With respect to the characteristics of fuzziness, complexity and uncertainty for many group-decision making problems in real world, the paper proposes a novel method based on the interval grey linguistic variables hybrid weighted harmonic aggregation operators to solve the multiple attribute group decision making problems in which the attribute values and the weights take the form of the interval grey linguistic variables. In the approach, the relative concepts and the operation rules of interval grey linguistic variables are defined, and some operators (such as interval grey linguistic weighted harmonic aggregation (IGLWHA) operator, interval grey linguistic ordered weighted harmonic aggregation (IGLOWHA) operator, and interval grey linguistic hybrid weighted harmonic aggregation (IGLHWHA) operator) are proposed to solve the group decision making problems. The computational results from an illustrative example have shown that the proposed approach is feasible and effective for the group-decision making problems.

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