A Three-Way Acceleration Approach for Interval-Valued Multi-Attribute Decision-Making Problems

As an essential part of modern intelligent decision-making science, multi-attribute problems can effectively select and rank all candidate schemes under multiple indicators. Because the complexity real environment uncertainty problem, interval numbers are often used to represent evaluation information object. The existing methods rarely use object set but give decision results by selection or ranking, which have strong subjectivity. We propose a ranking method from acceleration viewpoint based on three-way model solve interval-valued problem. A distance measure two objects is that describes relationship between objects. Therefore, fuzzy dominance introduced express order relations among First, we present compare any numbers, converts into connection according characteristics in problems. Second, theory divide high, medium, low regions for speed rationality decision-making. Finally, be simplified problem three selected region. Unlike traditional methods, experiments demonstrate our proposed has lowest cost. Our shown efficient obtain comparable results.