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07-06-2017 | Methodologies and Application

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

Authors: Yejun Xu, Cuiping Wei, Hao Sun

Published in: Soft Computing | Issue 14/2018

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Abstract

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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Title: Distance-based nonlinear programming models to identify and adjust inconsistencies for linguistic preference relations
Authors: Yejun Xu
Cuiping Wei
Hao Sun
Publication date: 07-06-2017
Publisher: Springer Berlin Heidelberg
Published in: Soft Computing / Issue 14/2018
Print ISSN: 1432-7643
Electronic ISSN: 1433-7479
DOI: https://doi.org/10.1007/s00500-017-2671-y

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