Consensus Building for the Heterogeneous Large-Scale GDM With the Individual Concerns and Satisfactions

TLDR

Large‑scale group decision‑making involves many participants with heterogeneous preference representations and individual concerns, making it hard to set a numerical consensus threshold. This study introduces a novel consensus‑reaching model tailored to heterogeneous large‑scale GDM that accounts for individual concerns and satisfactions. The model selects individual preference vectors, clusters decision makers, derives a group preference vector, defines a consensus measure that incorporates individual concerns, applies a linguistic approach to assess satisfaction, and employs a feedback adjustment process to refine preferences. A practical example and simulation analysis confirm the model’s validity.

Abstract

Nowadays, societal and technological trends demand the management of large scale of decision makers in group decision-making (GDM) contexts. In a large-scale GDM, decision makers often have individual concerns and satisfactions, and also they will use heterogeneous preference representation structures to express their preferences. Meanwhile, it is difficult to set the numerical consensus threshold to judge whether a consensus degree can be acceptable or not in the consensus reaching process in a large-scale GDM. This study proposes a novel consensus reaching model for the heterogeneous large-scale GDM with the individual concerns and satisfactions. In this consensus reaching model, a selection process is proposed to obtain the individual preference vectors, to divide decision makers into different clusters, and to yield the preference vector of the large group. Following this, a consensus measure method that considers the individual concerns on alternatives is defined for measuring the consensus degree, and a linguistic approach is developed to measure the individual and collective satisfactions regarding the consensus degree. Finally, a feedback adjustment process is proposed and utilized to help decision makers adjust their preferences. A practical example and a simulation analysis are presented to demonstrate the validity of the proposed consensus reaching model.