Single and interval valued neutrosophic group decision making problem based on dynamic programming cluster model.

In this study, we address the difficult group decision-making situations in which the preference data are represented by linguistic variables using the dynamic programming approach. Making decisions with exact numbers is difficult for decision-makers due to the ambiguity and complexity of reality. Since they cannot be computed directly, the language variables were encoded using single and interval neutrosophic sets. In a real-world context, neutrosophic sets are used to manage indeterminacy. Then, new models of similarity and distance are developed to quantify the relations between interval and single neutrosophic sets. Next, an interval-based clustering approach based on dynamic programming is proposed and used to group the decision-makers. In addition, a novel method is provided to calculate interval weights for decision-makers and clusters, considering both the cluster centre and group size. Next, a centroid-based ranking method is used to compare and rank the possibilities, and the effectiveness of the proposed strategy is demonstrated through illustrative trials. The purpose of the comparisons and discussions is to demonstrate its superiority. [ABSTRACT FROM AUTHOR]