Combination of unreliable evidence sources in intuitionistic fuzzy MCDM framework

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• 作者：Xiaodan Wang^a ; ^{afeu_wang@163.com" class="auth_mail" title="E-mail the corresponding author} ; Jingwei Zhu^a ; Yafei Song^a ; ^b ; ^{yafei_song@163.com" class="auth_mail" title="E-mail the corresponding author} ; Lei Lei^a
• 关键词：Dempster&ndash ; Shafer theory of evidence ; Atanassov's intuitionistic fuzzy set (AIFS) ; Multiple criteria decision making (MCDM) ; Reliability evaluation ; Evidence combination
• 刊名：Knowledge-Based Systems
• 出版年：2016
• 出版时间：1 April 2016
• 年：2016
• 卷：97
• 期：Complete
• 页码：24-39
• 全文大小：550 K

文摘

In this paper, we consider the combination of unreliable evidence sources in multiple criteria decision making (MCDM) framework in intuitionistic fuzzy environment. In the intuitionistic fuzzy MCDM framework, evidence sources can be combined based on intuitionistic fuzzy aggregation operators when reliability factors are known. Generalized intuitionistic fuzzy aggregation operators are applied to combine evidence sources with intuitionistic fuzzy reliability factors. Discounting operation on unreliable evidence bodies is also extended to deal with uncertain reliability factors. Then we define a combination operation on intuitionistic fuzzy values to combine evidence bodies in the intuitionistic fuzzy MCDM model. Finally the estimation of the reliability factors without prior knowledge is studied. Our proposed evaluation method is based on the principle of self-assessment. It is implemented by the probabilistic comparison between intuitionistic fuzzy values. Moreover, the proposed evaluation method is independent of the dissimilarity measure between basic probability assignments. Numerical examples demonstrate the performance of our combination rules and reliability estimation method.