期刊
INTERNATIONAL JOURNAL FOR UNCERTAINTY QUANTIFICATION
卷 7, 期 5, 页码 395-421出版社
BEGELL HOUSE INC
DOI: 10.1615/Int.J.UncertaintyQuantification.2017020416
关键词
similarity measure; combined weights; interval neutrosophic set; MABAC; EDAS
资金
- National Natural Science Foundation of China [61163036, 61462019]
- Shaoguan University [SY2016KJ11]
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 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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