Abstract
Aggregating decision-maker's evaluation and acquiring a ranking of alternatives is very important to multiple attribute decision making (MADM). In this paper, we propose a new method to solve MADM problems in which all the information provided by the decision-makers is presented as interval-valued intuitionistic fuzzy numbers (IVIFNs). In the method, IVIFNs are converted into a group of basic probability assignment (BPA) by continuous interval argument ordered weighted average (C-OWA) operator. And then evidence theory is applied to aggregate BPAs into a comprehensive BPA. Based on this single overall BPA, a ranking order of candidates can be obtained. Finally, a numerical example is used to illustrate the effectiveness of the proposed method.
Original language | English |
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Pages (from-to) | 595-601 |
Number of pages | 7 |
Journal | Journal of Computational Information Systems |
Volume | 10 |
Issue number | 2 |
DOIs | |
State | Published - 15 Jan 2014 |
Externally published | Yes |
Keywords
- Continuous interval argument ordered weighted average (C-OWA) operator
- Evidence theory
- Interval-valued intuitionistic fuzzy number (IVIFN)
- Multiple attribute decision making (MADM)