Dynamic Relationship Network Analysis Based on Louvain Algorithm for Large-Scale Group Decision Making

Authors

Minxuan Li¹, Jindong Qin^{1, *,} , Tao Jiang¹, Witold Pedrycz^{2, 3}

¹School of Management, Wuhan University of Technology, Wuhan, 430070, Hubei, China

²Department of Electrical and Computer Engineering, University of Alberta, Edmonton, Alberta, T6R 2V4, Canada

³System Research Institute, Polish Academy of Sciences, Warsaw, Poland

^*Corresponding author. Email: qinjindongseu@126.com

DOI

10.2991/ijcis.d.210329.001How to use a DOI?

Keywords

large-scale group decision making; consensus reaching process; dynamic relationship network; Louvain algorithm; node centrality; subgroup cohesion

Abstract

In most existing large-scale group decision making (LSGDM) problems, the relationships between decision makers (DMs) are usually ignored or regarded as static. However, in many cases, the results of LSGDM are dynamically influenced by the relationship between group members. To address this issue, a dynamic relationship network analysis method based on Louvain algorithm is proposed in this paper. First, each DM could be considered as a node to construct a relationship network, which dynamically change the individual opinion by the definition of correction index to eliminate subjective factors. Second, the node centrality and subgroup cohesion are defined and the Louvain algorithm is used to divide DMs into several subgroups to measure the importance of each node and subgroup. Then, the termination conditions of the discussion are determined by measuring the consensus and stability of the group decision information. Moreover, stage weight function is defined to assign weights to discussions at different stages and obtain the final results. An illustrative example is provided to prove the feasibility of the proposed model. Sensitivity analysis is given to show the stability of correction index and stage weight function. Finally, the comparative analysis is performed to illustrate its feasibility and effectiveness of the method.

Copyright

© 2021 The Authors. Published by Atlantis Press B.V.

Open Access

This is an open access article distributed under the CC BY-NC 4.0 license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - JOUR
AU  - Minxuan Li
AU  - Jindong Qin
AU  - Tao Jiang
AU  - Witold Pedrycz
PY  - 2021
DA  - 2021/04/06
TI  - Dynamic Relationship Network Analysis Based on Louvain Algorithm for Large-Scale Group Decision Making
JO  - International Journal of Computational Intelligence Systems
SP  - 1242
EP  - 1255
VL  - 14
IS  - 1
SN  - 1875-6883
UR  - https://doi.org/10.2991/ijcis.d.210329.001
DO  - 10.2991/ijcis.d.210329.001
ID  - Li2021
ER  -