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Multiplicative Consistency Ascertaining, Inconsistency Repairing, and Weights Derivation of Hesitant Multiplicative Preference Relations

Yejun Xu, Mengqi Li, Francisco Chiclana, Enrique Herrera‐Viedma

2021IEEE Transactions on Systems Man and Cybernetics Systems31 citationsDOIOpen Access PDF

Abstract

This article investigates multiplicative consistency ascertaining, inconsistency repairing, and weights derivation for hesitant multiplicative preference relations (HMPRs). First, the completely multiplicative consistency and weakly multiplicative consistency of HMPRs are defined. Based on them, 0–1 mixed programming models and simple algebraic operations are proposed to ascertain the multiplicative consistency of HMPRs. Then, some goal programming models are developed to generate the weights from consistent HMPRs and to revise inconsistent HMPRs. An integrated procedure to manage the multiplicative consistencies of HMPRs is designed. The proposed methods are also extended to accommodate incomplete HMPRs, and to estimate missing values. Finally, some numerical examples, a comparative analysis with existent approaches, and a simulation analysis are included to illustrate the practicality and effectiveness of the developed models.

Topics & Concepts

Multiplicative functionConsistency (knowledge bases)PreferenceMathematicsSimple (philosophy)Multiplicative inverseSequential consistencyApplied mathematicsComputer scienceMathematical optimizationAlgorithmStatisticsDiscrete mathematicsConsistency modelInversePhilosophyMathematical analysisGeometryCorrectnessEpistemologyOptimization and Mathematical ProgrammingMulti-Criteria Decision MakingBayesian Modeling and Causal Inference
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