Импакт фактор: 1.000
ISSN Печать: 2152-5080
Выпуски:Том 7, 2017 Том 6, 2016 Том 5, 2015 Том 4, 2014 Том 3, 2013 Том 2, 2012 Том 1, 2011
International Journal for Uncertainty Quantification
Algorithms for interval neutrosophic multiple attribute decision making based on MABAC, similarity measure and EDAS
In this paper, we define a new axiomatic definition of interval neutrosophic similarity measure, which is presented by interval neutrosophic number (INN). Later, the objective weights of various attributes are determined via Shannon entropy theory, meanwhile, we develop the combined weights, which can show both the subjective information and the objective information. Then, we present three approaches to solve interval neutrosophic decision making problems by Multi-Attributive Border Approximation area Comparison (MABAC), Evaluation based on Distance from Average Solution (EDAS) and similarity measure. Finally, the effectiveness and feasibility of algorithms are conceived by two illustrative examples.
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