A mean-area ranking based non-linear programming approach to solve intuitionistic fuzzy bi-matrix games

被引:11
|
作者
An, Jing-Jing [1 ]
Li, Deng-Feng [1 ]
Nan, Jiang-Xia [2 ]
机构
[1] Fuzhou Univ, Sch Econ & Management, Fuzhou 350108, Fujian, Peoples R China
[2] Guilin Univ Elect Technol, Sch Math & Comp Sci, Guangxi, Peoples R China
基金
中国国家自然科学基金;
关键词
Intuitionistic fuzzy number (IFN); mean-area ranking method; intuitionistic fuzzy bi-matrix game; intuitionistic fuzzy mathematical programming; SET THEORY; TERMINOLOGICAL DIFFICULTIES; DECISION-MAKING; BIMATRIX GAME; PAYOFFS; NUMBERS;
D O I
10.3233/JIFS-162299
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The aim of this paper is to develop a new methodology for solving bi-matrix games with payoffs of Atanassov's intuitionistic fuzzy (IF) numbers (IFNs), which are called IF bi-matrix games for short. In this methodology, we propose a weighted mean-area ranking method of IFNs, which is proven to satisfy the linearity. Hereby, the concept of Pareto optimal solution of IF bi-matrix games is introduced and the Pareto optimal solution can be obtained through solving the parameterized non-linear programming model, which is derived from an IF mathematical programming model based on the proposed weighted mean-area ranking method of IFNs. Validity and applicability of the model and method proposed in this paper are illustrated with a practical example of two commerce retailers' strategy choice problem.
引用
收藏
页码:563 / 573
页数:11
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