科研之友
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摘要
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.
- 出版日期2017
- 单位韶关学院
