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

摘要: Abstract Group decision making (GDM) problems require consensus reaching processes; however, these can be time consuming and costly. As experts change their evaluations after exchanging opinions being influenced by others, influences are spread across the various expert trust relationships. Because of experts’ knowledge limits, on alternatives relationships generally described using probabilistic linguistic terms. Therefore, to simplify process avoid bias, this paper proposes a particle swarm optimization method that incorporates relationship based social network for GDM under environment. Each is regarded as moves toward final evaluation reaches threshold. A fitness function built measure levels, updated improved derive new evaluations. numerical example then given illustrate feasibility proposed approach comparisons further elucidate its novelty validity.