Q‐Rung orthopair uncertain linguistic partitioned Bonferroni mean operators and its application to multiple attribute decision‐making method. Issue 10 (29th July 2019)

• Record Type: Journal Article
• Authors: Liu, Zhengmin; Li, Lin; Li, Junqing
• Is Part Of: International journal of intelligent systems. Volume 34:Issue 10(2019)
• Page Start: 2490
• Page End: 2520
• Publication Date: 2019-07-29
• Subjects: Bonferroni mean -- multiple‐attribute decision making -- partitioned Bonferroni mean -- q‐rung orthopair uncertain linguistic sets; Artificial intelligence -- Periodicals; Expert systems (Computer science) -- Periodicals; Intelligence artificielle -- Périodiques; Systèmes experts (Informatique) -- Périodiques; 006.3
• DOI: 10.1002/int.22158
• Languages: English
• ISSNs: 0884-8173

Abstract

Abstract: A q‐rung orthopair uncertain linguistic set can be served as an extension of an uncertain linguistic set (ULS) and a q‐rung orthopair fuzzy set, which can also be treated as a generalized form of the existing intuitionistic ULS and Pythagorean ULS. The new linguistic set uses the uncertain linguistic variable to express the qualitative evaluation information and allows decision makers to provide their true views freely in a larger membership grade space. In this paper, we investigate the Bonferroni mean under the q‐rung orthopair uncertain linguistic environment, then we propose the q‐rung orthopair uncertain linguistic Bonferroni mean and its weighted form. Furthermore, considering the specific partition pattern among the attributes, the q‐rung orthopair uncertain linguistic partitioned Bonferroni mean and its weighted form are developed. Meanwhile, we discuss several representative cases and attractive properties of our proposed operators in depth. Subsequently, a novel multi‐attribute decision‐making method is developed based on the above‐mentioned aggregation operators. In the end, a comprehensible case is performed to analyze the superiority of the developed method by comparing with other typical studies.