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

TL;DR

This paper introduces a novel grey interval relation TOPSIS method for multiple attribute decision-making that integrates subjective and objective interval grey weights and combines multiple relative approach degrees for improved decision accuracy.

Contribution

It presents a new hybrid grey interval relation decision-making approach that uniquely combines three relative degrees and uses a weighted Borda method for result integration.

Findings

Demonstrates applicability through an example case.

Effectively integrates subjective and objective weights.

Improves decision robustness with combined relative degrees.

Abstract

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.