A novel method for single-valued neutrosophic multi-criteria decision making with incomplete weight information

A single-valued neutrosophic set (SVNS) and an interval neutrosophic set (INS) are two instances of a neutrosophic set, which can efficiently deal with uncertain, imprecise, incomplete, and inconsistent information. In this paper, we develop a novel method for solving single-valued neutrosophic multi-criteria decision making with incomplete weight information, in which the criterion values are given in the form of single-valued neutrosophic sets (SVNSs), and the information about criterion weights is incompletely known or completely unknown. The developed method consists of two stages. The first stage is to use the maximizing deviation method to establish an optimization model, which derives the optimal weights of criteria under single-valued neutrosophic environments. After obtaining the weights of criteria through the above stage, the second stage is to develop a single-valued neutrosophic TOPSIS (SVNTOPSIS) method to determine a solution with the shortest distance to the single-valued neutrosophic positive ideal solution (SVNPIS) and the greatest distance from the single valued neutrosophic negative ideal solution (SVNNIS). Moreover, a best global supplier selection problem is used to demonstrate the validity and applicability of the developed method