NonLinear Programming Approach for Single-Valued Neutrosophic TOPSIS Method

We propose an approach for multi-attribute group decision-making (MAGDM) problems under neutrosophic information, where the preference values of alternatives over the attributes and the importance of attributes are expressed in terms of single-valued neutrosophic sets. Firstly, we develop a nonlinear programming approach based on Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method to determine relative closeness intervals of alternatives. Secondly, we aggregate closeness intervals to find out the ranking order of all alternatives by computing their optimal membership degrees based on the ranking method of interval numbers. Finally, we provide an illustrative example to show the effectiveness of the proposed approach.