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dc.contributor.authorGong, Zaiwu
dc.contributor.authorXu, Xiaoxia
dc.contributor.authorGuo, Weiwei
dc.contributor.authorHerrera Viedma, Enrique 
dc.contributor.authorCabrerizo Lorite, Francisco Javier 
dc.date.accessioned2024-12-18T07:34:18Z
dc.date.available2024-12-18T07:34:18Z
dc.date.issued2020
dc.identifier.citationPublished version: Z. Gong, et al. Minimum cost consensus modeling under various linear uncertain-constrained scenarios. Information Fusion 66 (2021) 1-17. doi: 10.1016/j.inffus.2020.08.015es_ES
dc.identifier.urihttps://hdl.handle.net/10481/98158
dc.descriptionThis work was supported by the National Natural Science Foundation of China (grant numbers 71971121, 71571104), NUIST-UoR International Research Institute, China, Spanish Ministry of Universities (grant number PID2019-103880RB-I00), the Graduate Research and Innovation Projects of Jiangsu Province (grant number SJKY19_0958), the Major Project Plan of Philosophy and Social Sciences Research in Jiangsu Universities (grant number 2018SJZDA038), and the impact of Weather Conditions on the Spread of Large-scale Influenza Virus, China (grant number 2020xtzx001).es_ES
dc.description.abstractGroup decision-making combined with uncertainty theory is verified as a more conclusive theory, by building a bridge between deterministic and indeterministic group decision-making in this paper. Due to the absence of sufficient historical data, reliability of decisions are mainly determined by experts rather than some prior probability distributions, easily leading to the problem of subjectivity. Thus, belief degree and uncertainty distribution are used in this paper to fit individual preferences, and five scenarios of uncertain chance-constrained minimum cost consensus models are further discussed from the perspectives of the moderator, individual decision-makers and non-cooperators. Through deduction, reaching conditions for consensus and analytic formulas of the minimum total cost are both theoretically given. Finally, with the application in carbon quota negotiation, the proposed models are demonstrated as a further extension of the crisp number or interval preference-based minimum cost consensus models. In other words, the basic conclusions of the traditional models are some special cases of the uncertain minimum cost consensus models under different belief degrees.es_ES
dc.description.sponsorshipNational Natural Science Foundation of China (71971121, 71571104)es_ES
dc.description.sponsorshipNUIST-UoR International Research Institute Chinaes_ES
dc.description.sponsorshipSpanish Ministry of Universities (PID2019-103880RB-I00)es_ES
dc.description.sponsorshipGraduate Research and Innovation Projects of Jiangsu Province (SJKY19_0958)es_ES
dc.description.sponsorshipJiangsu Universities (2018SJZDA038)es_ES
dc.description.sponsorshipChina (2020xtzx001)es_ES
dc.language.isoenges_ES
dc.publisherElsevieres_ES
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectGroup decision-makinges_ES
dc.subjectMinimum cost consensus modeles_ES
dc.subjectUncertainty theoryes_ES
dc.subjectLinear uncertainty distributiones_ES
dc.subjectBelief degreees_ES
dc.titleMinimum cost consensus modelling under various linear uncertain-constrained scenarioses_ES
dc.typejournal articlees_ES
dc.rights.accessRightsopen accesses_ES
dc.identifier.doi10.1016/j.inffus.2020.08.015
dc.type.hasVersionSMURes_ES


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