A self-management mechanism to manage noncooperative behaviors in LGDM-based supply chain risk mitigation
Metadatos
Mostrar el registro completo del ítemAutor
Zhao, Sihai; Dong, Yucheng; Zhang, Hengjie; Chiclana Parrilla, Francisco; Herrera Viedma, EnriqueEditorial
IEEE
Materia
Consensus reaching process Large-scale group decision making Non-cooperative behaviors Supply chain risk mitigation Self-management mechanism
Fecha
2018Referencia bibliográfica
S. Zhao, Y. Dong, H. Zhang, F. Chiclana and E. Herrera-Viedma, "A Self-Management Mechanism to Manage Non-cooperative Behaviors in LGDM-Based Supply Chain Risk Mitigation," 2018 IEEE International Conference on Systems, Man, and Cybernetics (SMC), Miyazaki, Japan, 2018, pp. 3307-3312, [doi: 10.1109/SMC.2018.00560]
Resumen
Large-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 selfmanagement
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.