Statistics

Complete information

Social psychology

Data mining

Computer science

Mathematical optimization

Missing data

Psychology

Preference

Mathematics

Fuzzy logic

Group decision-making

Artificial intelligence

Mathematical economics

Consistency (knowledge bases)

Machine learning

Computers & Industrial Engineering

Due to complicated decision environment and limited knowledge of decision makers, decision makers may provide incomplete hesitant fuzzy linguistic preference relations (IHFLPRs) in group decision making (GDM) problems. Furthermore, to guarantee that decision makers are non-random and logical and obtain decision results that are accepted by most decision makers, it is necessary to consider individual consistency control in consensus reaching processes (CRPs) for GDM problems. In this paper, some models are developed to manage incomplete information and consensus for GDM with IHFLPRs. First, we develop an optimization model to impute missing elements for an IHFLPR, in which the best additive consistency index (BCI) and the average additive consistency index (ACI) are utilized to measure the additive consistency level of an IHFLPR. Afterwards, for CRPs in GDM with IHFLPRs, some local adjustment strategy-based feedback adjustment rules are proposed to assist decision makers in modifying HFLPRs by considering the BCI and the ACI. Moreover, an iterative consensus reaching algorithm for GDM with IHFLPRs is further proposed. Eventually, a numerical example of 3D visualization management system selection for an automobile manufacturing enterprise is presented to elaborate the feasibility of the consensus reaching algorithm, and detailed numerical results are also provided to justify the algorithm.

Consensus reaching with consistency control in group decision making with incomplete hesitant fuzzy linguistic preference relations