Potential effect of uncertainty on the GRG interpretation

Abstract

Purpose

The purpose of this paper is to propose an interpretation of the grey relational grade taking into account its variation range on the basis of the error propagation theory.

Design/methodology/approach

The paper uses error propagation theory to calculate the uncertainty of the grey relational grade, exploring how errors are propagated through the sequential operations of the grey relational analysis.

Findings

The non‐consideration of the error associated to the measurement of the experimental data that is transferred to the grey relational grade may have a potential effect on the interpretation of the grey relational rank. Data uncertainty quantification provides information about how well measurement fits to the value of the measured quantity and determines its validity. Therefore, this might lead one to consider that some sequences are less attractive than other lower‐ranked ones.

Practical implications

The combination of the grey and error propagation theories is a tool to choose the most accurate solution in grey relational grade ranks.

Originality/value

This study provides a new approach to interpret grey relational grade classifications.

Citation

Saavedra, A., Arce, E., Luis Miguez, J. and Granada, E. (2013), "Potential effect of uncertainty on the GRG interpretation", Grey Systems: Theory and Application, Vol. 3 No. 2, pp. 121-128. https://doi.org/10.1108/GS-11-2012-0043