Multi-Attribute Decision-Making Model by Applying Grey Numbers

Informatica ◽  
2009 ◽  
Vol 20 (2) ◽  
pp. 305-320 ◽  
Author(s):  
Edmundas Kazimieras Zavadskas ◽  
Arturas Kaklauskas ◽  
Zenonas Turskis ◽  
Jolanta Tamošaitienė
Keyword(s):  
Decision Making ◽  
Multi Attribute Decision Making ◽  
Decision Making Model

Dynamic Multi-Attribute Decision Making Model with the Area Closeness Degree

2013 ◽  
Vol 321-324 ◽  
pp. 2557-2560
Author(s):  
Xi Juan Lou
Keyword(s):  
Decision Making ◽  
Ideal Solution ◽  
Raw Data ◽  
New Information ◽  
Multi Attribute Decision Making ◽  
Decision Making Model

The aim of this paper is to explore dynamic multi-attribute decision making (DMADM) problems in which the decision making information of alternatives is collected at different stages. Firstly, the area closeness degree is applied in normalizing the raw data. Secondly, the weights of different stages are determined by according to the principle of new information priority. The technique for preference by similarity to ideal solution (TOPSIS) is improved to aggregate the information from different stages. Finally, the example is illustrated to demonstrate the practicality and effectiveness of the proposed methods.

scholarly journals A Novel Decision-Making Model with Pythagorean Fuzzy Linguistic Information Measures and Its Application to a Sustainable Blockchain Product Assessment Problem

2019 ◽  
Vol 11 (20) ◽  
pp. 5630 ◽  
Author(s):  
Feifei Jin ◽  
Lidan Pei ◽  
Huayou Chen ◽  
Reza Langari ◽  
Jinpei Liu
Keyword(s):  
Decision Making ◽  
Similarity Measure ◽  
Membership Degree ◽  
Linguistic Information ◽  
Information Measures ◽  
New Information ◽  
Multi Attribute Decision Making ◽  
Product Assessment ◽  
Decision Making Model ◽  
Fuzzy Linguistic

This study presents a novel multi-attribute decision-making (MADM) model on the basis of Pythagorean fuzzy linguistic information measures. To do so, we first present a new concept of Pythagorean fuzzy linguistic sets to describe fuzziness and inconsistent information, in which the Pythagorean fuzzy linguistic values (PFLVs) are represented by the linguistic membership degree and linguistic non-membership degree. Then, we introduce two axiomatic definitions of information measures for PFLVs, including Pythagorean fuzzy linguistic entropy and the Pythagorean fuzzy linguistic similarity measure, to measure the uncertainty degree of PFLVs and the similarity degree between among PFLVs. In addition, based on the logarithmic function, we construct two new information measure formulas and verify that they satisfy the axiomatic conditions of the Pythagorean fuzzy linguistic entropy and similarity measure, respectively. We further explore the relationship between the Pythagorean fuzzy linguistic entropy and similarity measure. Finally, we present a novel Pythagorean fuzzy linguistic MADM model with the Pythagorean fuzzy linguistic entropy and similarity measure. A numerical example of selecting the most desirable sustainable blockchain product is given, and a comparison with the existing approach was performed to validate the reliability of the developed decision-making model.

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