Todim decision making method based on entropy and projection measure in neutrosophic-Z sets

Neutrosophic sets, developed by Smarandache, define the membership of an element to a set with three components: truth, uncertainty and falsity. These membership functions take values in the range [0,1] and their sum can exceed 1. Neutrosophic sets generalize classical and fuzzy sets, allowing for more flexible modeling of uncertainty and contradiction. The Z-numbers proposed by Zadeh better express both the knowledge of the data and the reliability of that knowledge. However, in environments with uncertainty and inconsistency, knowledge has limitations in terms of reliability. The Neutrosophic-Z set (NZS) proposed by Du et al. overcomes this limitation by considering not only the degrees of accuracy, uncertainty and inaccuracy, but also the degree of reliability of each of them separately. In this way, NZSs enable more reliable results by better modeling uncertainties in decision-making processes. Although these sets are an important tool in decision-making processes, NZS-based information measures are limited in the existing literature. In this thesis, an entropy-based normalized projection measure on NZSs has been developed. Then, using this proposed projection measure, the framework of the TODIM method, one of the multi-criteria decision-making methods, has been developed within the framework of NZSs. The effectiveness of the proposed method has been demonstrated in the process of venture capitalists determining which venture to invest in. In addition, the functionality and advantages of the developed method have been discussed by comparing it with related methods.