Particle swarm optimization for trust relationship based social network group decision making under a probabilistic linguistic environment

作者：

Highlights：

• The trust relationships between experts are considered in group decision making.

• The social network is used to determine the adjustment coefficients in consensus reaching process.

• The fitness function of PSO algorithm is improved under a probabilistic linguistic environment.

• Consensus reaching process is simulated with PSO algorithm.

摘要

•The trust relationships between experts are considered in group decision making.•The social network is used to determine the adjustment coefficients in consensus reaching process.•The fitness function of PSO algorithm is improved under a probabilistic linguistic environment.•Consensus reaching process is simulated with PSO algorithm.

论文关键词：Group decision making (GDM),Trust,Particle swarm optimization (PSO),Probabilistic linguistic term set (PLTS),Consensus reaching process (CRP)

论文评审过程：Received 14 October 2019, Revised 30 April 2020, Accepted 1 May 2020, Available online 7 May 2020, Version of Record 16 May 2020.

论文官网地址：https://doi.org/10.1016/j.knosys.2020.105999