Distance-based nonlinear programming models to identify and adjust inconsistencies for linguistic preference relations

被引：10
|
作者：
Xu, Yejun [1 ]
Wei, Cuiping [2 ]
Sun, Hao [3 ]
机构：
[1] Hohai Univ, Sch Business, Nanjing 211100, Jiangsu, Peoples R China
[2] Yangzhou Univ, Coll Math Sci, Yangzhou 225002, Jiangsu, Peoples R China
[3] Qingdao Univ, Sch Business, Qingdao 266071, Peoples R China
来源：
SOFT COMPUTING | 2018年 / 22卷 / 14期
基金：
中国国家自然科学基金;
关键词：
Ordinal consistency; Additive consistency; Linguistic preference relation; Distance; Nonlinear programming; GROUP DECISION-MAKING; CONSENSUS SUPPORT-SYSTEM; AGGREGATION OPERATORS; CONSISTENCY;
D O I：
10.1007/s00500-017-2671-y
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
This paper studies the ordinal and additive inconsistency problems of linguistic preference relations. First, the definition of ordinal consistency of a linguistic preference relation is proposed. Based on the definition of adjacency matrix of a linguistic preference relation, the necessary and sufficient conditions of a linguistic preference relation being ordinally consistent are given. Then, a distance-based nonlinear programming method is developed to identify and adjust the ordinal and additive inconsistencies for linguistic preference relations. The proposed methods can not only solve the ordinal inconsistency, additive inconsistency problems, respectively, but also solve the ordinal and additive inconsistency problems simultaneously. Finally, numerical examples and comparative analysis are provided to show the effectiveness and advantages of the proposed methods.
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页码：4833 / 4849
页数：17
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