An improved Taguchi multi-criteria decision-making method based on the hesitant fuzzy correlation coefficient and its application in quality evaluation

Abstract

This article is aimed at exploring an improved Taguchi SNR technique to settle the problem of multi-criteria decision-making (MCDM) in a hesitant fuzzy situation. Firstly, a novel correlation coefficient is defined under message from hesitant fuzzy sets and a weighted correlation coefficient proposed to deal with uncertainty. On that basis, several hesitant fuzzy correlation SNR measures are proposed in terms of the use of the weighted correlation coefficient. These measures cannot only avoid information distortion and omission, but are more sensitive when small datasets are used to reduce computational burden and reflect the correlation conflict in the process of information processing. Then, a hesitant fuzzy Taguchi method is proposed based on a novel weighted correlation coefficient which follows the principle of compromise such that the difference between the selected alternatives and the average solution is minimised to determine the optimal alternatives under the framework of the Taguchi method. The established method considers association conflict and provides a flexible and effective method for solving MCDM problems in a hesitant fuzzy environment. The implementation and the rationality process of the proposed method are demonstrated by an example pertinent to quality evaluation of tourism city development and compared outputs therefrom with four similar methods.