On three perspectives for deriving three-way decision with linguistic intuitionistic fuzzy information

被引:38
|
作者
Liu, Jiubing [1 ]
Mai, Jiaxin [2 ]
Li, Huaxiong [3 ]
Huang, Bing [4 ]
Liu, Yongjun [5 ]
机构
[1] Shantou Univ, Sch Business, Shantou 515063, Guangdong, Peoples R China
[2] Shantou Univ, Shantou Univ Med Coll, Shantou 515063, Guangdong, Peoples R China
[3] Nanjing Univ, Sch Management & Engn, Nanjing 210093, Peoples R China
[4] Nanjing Audit Univ, Sch Informat Engn, Nanjing 211815, Peoples R China
[5] South China Univ Technol, Sch Business Adm, Guangzhou 510641, Peoples R China
关键词
Three-way decision; Linguistic intuitionistic fuzzy numbers; Linguistic intuitionistic fuzzy decision-; theoretic rough sets; KKT condition; Single optimization model; ROUGH SETS; MODEL;
D O I
10.1016/j.ins.2021.12.072
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The determination of both thresholds in decision-theoretic rough sets is an important problem of study that has aroused widespread attention in recent years. Although many related methods have been proposed, they may need a substantial amount of computation in model solving even not capture the thresholds in some cases. In this paper, we introduce linguistic intuitionistic fuzzy numbers (LIFNs) into loss functions due to LIFNs integrating the advantages of linguistic terms and intuitionistic fuzzy numbers, and propose a single optimization model-based, threshold-determined method to derive three-way decision. First, we define a novel measure for ranking LIFNs, verify its properties, analyze the relationships between loss functions with LIFNs and establish linguistic intuitionistic fuzzy decision-theoretic rough sets with a novel measure for LIFNs. Second, we investigate linguistic intuitionistic fuzzy, three-way decision methods from three perspectives, especially from the third perspective. We construct a single optimization model for capturing the thresholds that can overcome the shortcomings of the methods from two other perspectives, and the uniqueness of the optimal solution of this model is proven with the aid of the Karush-Kuhn-Tucker (KKT) condition. Third, a single model-based perspective method and its corresponding algorithm are designed to determine the thresholds for linguistic intuitionistic fuzzy information. Last, an illustrative example and simulated experiments are conducted to show the validity of our method. (c) 2021 Elsevier Inc. All rights reserved.
引用
收藏
页码:350 / 380
页数:31
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