A multi-attribute decision-making model for the robust classification of multiple inputs and outputs datasets with uncertainty

2016 ◽  
Vol 38 ◽  
pp. 176-189 ◽  
Author(s):  
Kuang Yu Huang ◽  
I-Hui Li
Keyword(s):  
Decision Making ◽  
Robust Classification ◽  
Multi Attribute Decision Making ◽  
Decision Making Model ◽  
Inputs And Outputs

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.

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