An approach of TOPSIS technique for developing supplier selection with group decision making under type-2 neutrosophic number - Abdel-Basset, Mohamed; Saleh, M.; Gamal, Abduallah; Smarandache, Florentin (Applied soft computing, 2019)
This paper proposes an advanced type of neutrosophic technique, called type 2 neutrosophic numbers, and defines some of its operational rules. The type 2 neutrosophic number weighted averaging operator is determined in order to collective the type 2 neutrosophic number set, inferring some properties of the suggested operator. The operator is employed in a MADM problem to collect the type 2 neutrosophic numbers based classification values of each alternative over the features. The convergent classification values of every alternative are arranged with the assistance of score and accuracy values with the aim to detect the superior alternative. We introduce an illuminating example to confirm the suggested approach for multi attribute decision making issues, ordering the alternatives based on the accuracy function. Selecting an appropriate alternative among the selection options is a difficult activity for decision makers, since it is complicated to express attributes as crisp numbers. To tackle the problem, type 2 neutrosophic numbers can be efficiently used to estimate information in the decision making process. The type 2 neutrosophic numbers can accurately describe real cognitive information. We propose a novel T2NN-TOPSIS strategy combining type 2 neutrosophic numbers and TOPSIS under group decision making as application of T2NN, suggesting a type 2 neutrosophic number expression for linguistic terms. Finally, we provide a real case dealing with a decision making problem based on the proposed T2NN-TOPSIS methodology to prove the efficiency and the applicability of the type 2 neutrosophic number. •An advanced type of neutrosophic technique, called T2NN is proposed.•Some desirable properties and peculiar forms of operators are investigated.•The type 2 neutrosophic numbers can accurately describe real cognitive information.•A real case study based on the proposed T2NN-TOPSIS is introduced.