Prioritization and Aggregation of Intuitionistic Preference Relations: A Multiplicative-Transitivity-Based Transformation from Intuitionistic Judgment Data to Priority Weights

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• 作者：Yibin Zhang ; Kevin W. Li ; Zhou-Jing Wang
• 关键词：Intuitionistic preference relation (IPR) ; Multiplicative consistency ; Intuitionistic fuzzy weight ; Aggregation ; Linear programming
• 刊名：Group Decision and Negotiation
• 出版年：2017
• 出版时间：March 2017
• 年：2017
• 卷：26
• 期：2
• 页码：409-436
• 全文大小：
• 刊物类别：Business and Economics
• 刊物主题：Operation Research/Decision Theory; Social Sciences, general;
• 出版者：Springer Netherlands
• ISSN：1572-9907
• 卷排序：26

文摘

This article proposes a goal programming framework for deriving intuitionistic fuzzy weights from intuitionistic preference relations (IPRs). A new multiplicative transitivity is put forward to define consistent IPRs. By analyzing the relationship between intuitionistic fuzzy weights and multiplicative consistency, a transformation formula is introduced to convert normalized intuitionistic fuzzy weights into multiplicative consistent IPRs. By minimizing the absolute deviation between the original judgment and the converted multiplicative consistent IPR, two linear goal programming models are developed to obtain intuitionistic fuzzy weights from IPRs for both individual and group decisions. In the context of multicriteria decision making with a hierarchical structure, a linear program is established to obtain a unified criterion weight vector, which is then used to aggregate local intuitionistic fuzzy weights into global priority weights for final alternative ranking. Two numerical examples are furnished to show the validity and applicability of the proposed models.