@misc{10481/69532,
year = {2021},
month = {2},
url = {http://hdl.handle.net/10481/69532},
abstract = {In real-life group decision-making (GDM) problems, the preferences given by decision-makers(DMs)
are often incomplete, because the complexity of decision-making problems and the limitation of
knowledge of DM make it difficult for DMs to take a determined evaluation of alternatives. In
addition, preference relations provided by DMs are often heterogeneous because they always have
different decision habits and hobbies. However, the consensus method for GDM under incomplete
heterogeneous preference relations is rarely studied. For four common preference relations: utility
values, preference orderings, and (incomplete) multiplicative preference relations and (incomplete)
fuzzy preference relations, this paper proposes a geometrical method for consensus building in GDM.
Specifically, we integrate incomplete heterogeneous preference structures using a similarity-based
optimization model and set a corresponding geometrical consensus measurement. Then, preference
modification and weighting processes are proposed to improve consensus degree. Finally, we conduct
a comparison analysis based on a qualitative analysis and algorithm complexity analysis of existing
consensus reaching methods. Numerical analyses and convergence tests show that our method can
promote the improvement of the consensus degree in GDM, and has less time complexity than the
previous methods. The proposed geometrical method is a more explainable model due to operability
and simplicity.},
organization = {National Natural Science Foundation of China (NSFC)

71874023
71725001
71910107002
71771037
71971042},
organization = {European Regional Development Fund (FEDER), European Union 

TIN2016-75850-R},
publisher = {Elsevier},
keywords = {Group decision making},
keywords = {Consensus reaching},
keywords = {Incomplete heterogeneous preference structures},
keywords = {Geometrical method},
title = {A geometrical method for consensus building in GDM with incomplete heterogeneous preference information},
doi = {10.1016/j.asoc.2021.107224},
author = {Kou, Gang and Peng, Yi and Chao, Xiangrui and Herrera Viedma, Enrique and Alsaadi, Fawaz E.},
}