4.6 Article

Approaches to single-valued neutrosophic MADM based on MABAC, TOPSIS and new similarity measure with score function

Journal

NEURAL COMPUTING & APPLICATIONS
Volume 29, Issue 10, Pages 939-954

Publisher

SPRINGER LONDON LTD
DOI: 10.1007/s00521-016-2607-y

Keywords

Similarity measure; SVNN; Score function; Combined weighed; TOPSIS; MABAC

Funding

  1. National Natural Science Foundation of China [61163036]

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In this paper, we initiate a new axiomatic definition of single-valued neutrosophic distance measure and similarity measure, which is expressed by single-valued neutrosophic number that will reduce the information loss and remain more original information. Meanwhile, a novel score function is proposed. Then, the objective weights of various attributes are determined via gray system theory. Moreover, we present the combined weights, which can show both the subjective information and the objective information. Later, we present three algorithms to deal with multi-attribute decision-making problem based on revised Technique for Order Preference by Similarity to an Ideal Solution, Multi-Attributive Border Approximation area Comparison and similarity measure. Finally, the effectiveness and feasibility of approaches are demonstrated by two numerical examples.

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