Yazarlar
- Şahin, Rıdvan(2)
- Liu, Peide(1)
Yayınlar
- MakaleYalnız künye2017Scopus SJRQ1Cross-entropy measure on interval neutrosophic sets and its applications in multicriteria decision making
Şahin, Rıdvan
The neutrosophic set model is an important tool for dealing with real scientific and engineering applications because it can handle not only incomplete information but also the inconsistent information and indeterminate information which exist commonly in real situations. In this paper, we firstly propose two practical techniques converting an interval neutrosophic set into a fuzzy set and a single-valued neutrosophic set, respectively. Then, we define the interval neutrosophic cross-entropy in two different ways, which are based on extension of fuzzy cross-entropy and single-valued neutrosophic cross-entropy. Additionally, two multicriteria decision-making methods using the interval neutrosophic cross-entropy between an alternative and the ideal alternative are developed in order to determine the order of the alternatives and choose most preferred one(s). Finally, an illustrative example is presented to verify the proposed methods and to demonstrate their effectiveness and practicality.
AtıfScopus65WoS62OpenAlex72
İncele - MakaleAçık Erişim2016Scopus SJRQ2Maximizing deviation method for neutrosophic multiple attribute decision making with incomplete weight information
Şahin, Rıdvan; Liu, Peide
This paper develops a method for solving the multiple attribute decision-making problems with the single-valued neutrosophic information or interval neutrosophic information. We first propose two discrimination functions referred to as score function and accuracy function for ranking the neutrosophic numbers. An optimization model to determine the attribute weights that are partly known is established based on the maximizing deviation method. For the special situations where the information about attribute weights is completely unknown, we propose another optimization model. A practical and useful formula which can be used to determine the attribute weights is obtained by solving a proposed nonlinear optimization problem. To aggregate the neutrosophic information corresponding to each alternative, we utilize the neutrosophic weighted averaging operators which are the single-valued neutrosophic weighted averaging operator and the interval neutrosophic weighted averaging operator. Thus, we can determine the order of alternatives and choose the most desirable one(s) based on the score function and accuracy function. Finally, some illustrative examples are presented to verify the proposed approach and to present its effectiveness and practicality.
AtıfScopus151WoS130OpenAlex148İncele