RT Journal Article ID 07083a2f36b8018c A1 Peng, Xindong A1 Dai, Jingguo T1 ALGORITHMS FOR INTERVAL NEUTROSOPHIC MULTIPLE ATTRIBUTE DECISION-MAKING BASED ON MABAC, SIMILARITY MEASURE, AND EDAS JF International Journal for Uncertainty Quantification JO IJUQ YR 2017 FD 2017-09-20 VO 7 IS 5 SP 395 OP 421 K1 similarity measure K1 combined weights K1 interval neutrosophic set K1 MABAC K1 EDAS AB 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 subjective information and objective information. Then, we present three approaches to solve interval neutrosophic decision-making problems by multiattributive 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. PB Begell House LK https://www.dl.begellhouse.com/journals/52034eb04b657aea,468587191a97aaba,07083a2f36b8018c.html