Novel Grey Interval Weight Determining and Hybrid Grey Interval Relation Method in Multiple Attribute Decision-Making

07/11/2012
by   Gol Kim, et al.
0

This paper proposes a grey interval relation TOPSIS for the decision making in which all of the attribute weights and attribute values are given by the interval grey numbers. The feature of our method different from other grey relation decision-making is that all of the subjective and objective weights are obtained by interval grey number and that decisionmaking is performed based on the relative approach degree of grey TOPSIS, the relative approach degree of grey incidence and the relative membership degree of grey incidence using 2-dimensional Euclidean distance. The weighted Borda method is used for combining the results of three methods. An example shows the applicability of the proposed approach.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
07/17/2012

Hybrid Grey Interval Relation Decision-Making in Artistic Talent Evaluation of Player

This paper proposes a grey interval relation TOPSIS method for the decis...
research
07/06/2012

Super-Mixed Multiple Attribute Group Decision Making Method Based on Hybrid Fuzzy Grey Relation Approach Degree

The feature of our method different from other fuzzy grey relation metho...
research
03/15/2017

Aggregation of Classifiers: A Justifiable Information Granularity Approach

In this study, we introduce a new approach to combine multi-classifiers ...
research
07/06/2012

Generalized Hybrid Grey Relation Method for Multiple Attribute Mixed Type Decision Making

The multiple attribute mixed type decision making is performed by four m...
research
01/04/2022

A integrating critic-waspas group decision making method under interval-valued q-rung orthogonal fuzzy enviroment

This paper provides a new tool for multi-attribute multi-objective group...
research
06/28/2019

Improving and benchmarking of algorithms for decision making with lower previsions

Maximality, interval dominance, and E-admissibility are three well-known...

Please sign up or login with your details

Forgot password? Click here to reset