@misc{10481/77961,
year = {2014},
url = {https://hdl.handle.net/10481/77961},
abstract = {A visual consensus feedback mechanism for group decision
making (GDM) problems with complementary linguistic preference rela-
tions is presented. Linguistic preferences are modelled using triangular
fuzzy membership functions, and the concepts of similarity degree (SD)
between two experts as well as the proximity degree (PD) between an
expert and the rest of experts in the group are de ned and used to
measure the consensus level (CL). A feedback mechanism is proposed to
identify experts, alternatives and corresponding preference values that
contribute less to consensus. The novelty of this feedback mechanism
is that it provides experts with visual representations of their consen-
sus status to easily `see' their consensus position within the group as
well as to identify the alternatives and preference values that should be
reconsidered for changing in the subsequent consensus round. The feed-
back mechanism also includes individualised recommendations to those
identi ed experts on changing their identi ed preference values and vi-
sual graphical simulation of future consensus status if the recommended
values were to be implemented.},
organization = {European Commission	TIN2010-17876},
organization = {Andalusian Excellence	TIC-05299	
TIC-5991},
organization = {University of Granada Excellence},
organization = {National Natural Science Foundation of China (NSFC)	71101131	
713311002	
LR13G010001},
publisher = {Springer},
keywords = {Group decisions making},
keywords = {Consensus},
keywords = {Linguistic preferences},
keywords = {Visual feedback mechanism},
keywords = {Inteligencia artificial},
keywords = {Artificial intelligence},
title = {Visual consensus feedback mechanism for group decision making with complementary linguistic preference relations},
author = {Chiclana Parrilla, Francisco and Herrera Viedma, Enrique},
}