A Multi-attribute Decision-making Method for Probabilistic Language VIKOR Based on Correlation Coefficient and Entropy

This paper proposes extending the VIKOR technique to the Probabilistic Linguistic Term Set (PLTS) to address the issue of retaining even more assessment information as possible while reasonably calculating the weights of experts and characteristics in the multi-attribute decision-making issue. Initially, a new PLTS aggregation method is recommended; then the model PLTS is constructed through the correlation coefficient weights and the weights based on entropy measures, and the objective weights of the experts and the objective weights of the attributes are obtained; secondly, the VIKOR method is extended to PLTS, The alternatives are ranked and the best one is selected considering the subjective preferences of decision makers; finally, through comparison analysis and further green supplier instances, the method's viability and efficacy are confirmed.