Computational aspects of neutrosophic multi attribute decision making problems

Abstract

Multi Attribute Decision Making (MADM) a commonly known problem in decision theory involves the process of making decisions over the available alternatives that are characterized by multiple, usually conflicting attributes. MADM is an important research field in decision science and Operations Research, which has been widely applied in many domains, such as investment decision, project evaluation, selection of optimum plan, economic efficiency and quality synthetic evaluation. For catching up imprecise or vague information, the ratings of alternatives with respect to each attribute are considered as single valued neutrosophic numbers. The main objective of this research work is to develop a multi attribute decision making method under neutrosophic environment using various approaches, namely, aggregation of the ratings, entropy weight of the attributes, subjective weight of the attributes (LINMAP) and TOPSIS. In this study, the researcher has proposed new harmonic averaging operators such as, Single Valued Trapezoidal Neutrosophic Ordered Weighted Harmonic Averaging (SVTNOWHA) operator, Single Valued Triangular Neutrosophic Generalized Ordered Weighted Harmonic Averaging (SVTrNGOWHA) operator, Single Valued Trapezoidal Neutrosophic Generalized Ordered Weighted Harmonic Averaging (SVTNGOWHA) operator, Single Valued Triangular Neutrosophic Generalized Weighted Harmonic Averaging (SVTrNGWHA) operator and Single Valued Trapezoidal Neutrosophic Generalized Weighted Harmonic Averaging (SVTNGWHA) operator, all of which can be used for aggregating the single newline