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Softmax Function Based Neutrosophic Aggregation Operators and Application in Multi-Attribute Decision Making Problem


 Softmax function is a well-known generalization of the logistic function. It has been extensively used in various probabilistic classification methods such as softmax regression, linear discriminant analysis, naive bayes classifiers, and artificial neural networks. Inspired by the advantages of softmax function, we focused on this paper is to develop the softmax function based single valued neutrosophic aggregation operators. Then we have established some essential properties of aggregation operators based on softmax function with neutrosophic set. Additionally, we have defined a multi-attribute decision making method based on the proposed aggregation operators. Using this MADM method we exercised a realistic MADM problem with neutrosophic informations. Finally, we checked the validity and reliability of the proposed methods considering by one numerical illustration.