Multiplicative Consistency Ascertaining, Inconsistency Repairing, and Weights Derivation of Hesitant Multiplicative Preference Relations Xu, Yejun Chiclana Parrilla, Francisco Herrera Viedma, Enrique Consistency ascertaining Hesitant multiplicative preference relations (HMPRs) Inconsistency repairing Missing values Weights derivation This work was supported in part by the National Natural Science Foundation of China (NSFC) under Grant 71871085, and in part by FEDER Funds provided in the National Spanish Project under Grant PID2019-103880RB-I00. 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. 2022-01-24T11:11:55Z 2022-01-24T11:11:55Z 2021-07-19 info:eu-repo/semantics/article Published version: Y. Xu... [et al.]. "Multiplicative Consistency Ascertaining, Inconsistency Repairing, and Weights Derivation of Hesitant Multiplicative Preference Relations," in IEEE Transactions on Systems, Man, and Cybernetics: Systems, doi: [10.1109/TSMC.2021.3099862] http://hdl.handle.net/10481/72453 10.1109/TSMC.2021.3099862 eng http://creativecommons.org/licenses/by-nc-nd/3.0/es/ info:eu-repo/semantics/openAccess AtribuciĆ³n-NoComercial-SinDerivadas 3.0 EspaƱa IEEE