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dc.contributor.authorZhao, Sihaien
dc.contributor.authorDong, Yuchengen
dc.contributor.authorZhang, Hengjieen
dc.contributor.authorChiclana, Franciscoen
dc.contributor.authorHerrera-Viedma, Enriqueen
dc.date.accessioned2019-03-14T12:44:24Z
dc.date.available2019-03-14T12:44:24Z
dc.date.issued2019-01-17
dc.identifier.citationZhao, S., Dong, Y., Zhang, H., Chiclana, F., Herrera-Viedma, E. (2018) A Self-Management Mechanism to Manage Non-cooperative Behaviors in LGDM-Based Supply Chain Risk Mitigation. Proceedings of the 2018 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2018, article. no. 8616557, pp. 3307-3312.en
dc.identifier.isbn9781538666500
dc.identifier.issn2577-1655
dc.identifier.urihttp://hdl.handle.net/2086/17623
dc.descriptionThe file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.en
dc.description.abstractLarge-scale group decision making (LGDM) is becoming more and more common, and how to assure the security and quality of the decision making process has become a hot topic. Supply chain risk mitigation is a complex LGDM problem involving in many stakeholders. In the decision making process, a group of experts aims at reaching a consensus among alternatives in which non-cooperative behaviors often appear. Some experts might designedly form a small alliance and change their preferences in a direction against consensus with the aim to foster the alliance’s own interests. In this study, we present a novel large-scale consensus reaching framework based on a self- management mechanism to manage non-cooperative behaviors. In the proposed framework, experts are classified into different subgroups using a clustering method, and they provide their evaluation information, i.e., the multi-criteria mutual evaluation matrices (MCMEMs), regarding the obtained subgroups based on their performance. The subgroups’ weights are generated dynamically from the MCMEMs, which are in turn used to update experts’ weights. This mechanism allows penalizing the weights of the experts with non-cooperative behaviors. Detailed comparison analysis is presented to verify the validity of the proposed consensus framework for supply chain risk mitigation.en
dc.language.isoenen
dc.publisherIEEE Xploreen
dc.subjectconsensus reaching processen
dc.subjectlarge-scale group decision makingen
dc.subjectnon-cooperative behaviorsen
dc.subjectsupply chain risk mitigationen
dc.titleA Self-Management Mechanism to Manage Non-cooperative Behaviors in LGDM-Based Supply Chain Risk Mitigationen
dc.typeConferenceen
dc.identifier.doihttps://doi.org/10.1109/SMC.2018.00560
dc.researchgroupInstitute of Artificial Intelligence (IAI)en
dc.peerreviewedYesen
dc.funderN/Aen
dc.projectidN/Aen
dc.cclicenceCC-BY-NC-NDen
dc.date.acceptance2018-06-15en
dc.researchinstituteInstitute of Artificial Intelligence (IAI)en


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