A multi-attribute decision making method based on evidence theory and average operator

被引：0
|
作者：
Li, Ya [1 ]
Shu, Gang [2 ]
Deng, Xinyang [1 ]
Deng, Yong [1 ,3 ]
机构：
[1] School of Computer and Information Science, Southwest University, Chongqing 400715, China
[2] School of Physical Science and Technology, Southwest University, Chongqing 400715, China
[3] School of Engineering, Vanderbilt University, Nashville TN 37235, United States
来源：
Journal of Computational Information Systems | 2014年 / 10卷 / 02期
关键词：
Decision making - Numerical methods - Decision theory - Fuzzy rules;
D O I：
10.12733/jcis8924
中图分类号：
学科分类号：
摘要：
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. Copyright © 2014 Binary Information Press.
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页码：595 / 601
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