Application of prioritized aggregation operators in preference voting

2010 ◽  
Vol 25 (10) ◽  
pp. 1027-1034 ◽  
Author(s):  
Gholam R. Amin ◽  
Hamid Sadeghi
Keyword(s):  
Aggregation Operators ◽  
Preference Voting ◽  
Prioritized Aggregation Operators

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 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.

scholarly journals MADM Based on Generalized Interval Neutrosophic Schweizer-Sklar Prioritized Aggregation Operators

Symmetry ◽  
2019 ◽  
Vol 11 (10) ◽  
pp. 1187 ◽  
Author(s):  
Khan ◽  
Abdullah ◽  
Mahmood ◽  
Naeem ◽  
Rashid
Keyword(s):  
Decision Making ◽  
Variable Parameter ◽  
Information Aggregation ◽  
Aggregation Operators ◽  
Weighted Averaging ◽  
Neutrosophic Set ◽  
High Tech ◽  
Operational Laws ◽  
Multiple Attribute ◽  
Prioritized Aggregation Operators

The interval neutrosophic set (INS) can make it easier to articulate incomplete, indeterminate, and inconsistent information, and the Schweizer-Sklar (Sh-Sk) t-norm (tm) and t-conorm (tcm) can make the information aggregation process more flexible due to a variable parameter. To take full advantage of INS and Sh-Sk operations, in this article, we expanded the Sh-Sk and to IN numbers (INNs) in which the variable parameter takes values from , develop the Sh-Sk operational laws for INNs and discussed its desirable properties. After that, based on these newly developed operational laws, two types of generalized prioritized aggregation operators are established, the generalized IN Sh-Sk prioritized weighted averaging (INSh-SkPWA) operator and the generalized IN Sh-Sk prioritized weighted geometric (INSh-SkPWG) operator. Additionally, we swot a number of valuable characteristics of these intended aggregation operators (AGOs) and created two novel decision-making models to match with multiple-attribute decision-making (MADM) problems under IN information established on INSh-SkPWA and INSh-SkPRWG operators. Finally, an expressive example regarding evaluating the technological innovation capability for the high-tech enterprises is specified to confirm the efficacy of the intended models.

UNCERTAIN LINGUISTIC PRIORITIZED AGGREGATION OPERATORS AND THEIR APPLICATION TO MULTIPLE ATTRIBUTE GROUP DECISION MAKING

2013 ◽  
Vol 21 (04) ◽  
pp. 603-627 ◽  
Author(s):  
L. Y. ZHOU ◽  
R. LIN ◽  
X. F. ZHAO ◽  
G. W. WEI
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Aggregation Operators ◽  
Linguistic Information ◽  
Priority Level ◽  
Multiple Attribute ◽  
Prioritized Aggregation Operators ◽  
Magdm Problems

In this paper, we investigate the uncertain linguistic multiple attribute group decision making (MAGDM) problems in which the attributes and experts are in different priority level. Motivated by the idea of prioritized aggregation operators (R. R. Yager, Prioritized aggregation operators, Int. J. Approximate Reasoning48 (2008) 263–274.), we develop some prioritized aggregation operators for aggregating uncertain linguistic information, and then apply them to develops some models for uncertain linguistic multiple attribute group decision making (MAGDM) problems in which the attributes and experts are in different priority level. Finally, a practical example about talent introduction is given to verify the developed approach and to demonstrate its practicality and effectiveness.

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