@misc{10481/64980,
year = {2018},
url = {http://hdl.handle.net/10481/64980},
abstract = {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.},
publisher = {IEEE},
keywords = {Consensus reaching process},
keywords = {Large-scale group decision making},
keywords = {Non-cooperative behaviors},
keywords = {Supply chain risk mitigation},
keywords = {Self-management mechanism},
title = {A self-management mechanism to manage noncooperative behaviors in LGDM-based supply chain risk mitigation},
doi = {10.1109/SMC.2018.00560},
author = {Zhao, Sihai and Dong, Yucheng and Zhang, Hengjie and Chiclana Parrilla, Francisco and Herrera Viedma, Enrique},
}