Probabilistic linguistic GRA method for multiple attribute group decision making

In practical multiple attribute group decision making (MAGDM) issues, uncertain and fuzzy cognitive decision information is well-depicted by linguistic term sets (LTSs). These LTSs are easily shifted into probabilistic linguistic sets (PLTSs). In such paper, a grey relational analysis (GRA) method is investigated to tackle probabilistic linguistic MAGDM with completely unknown attribute weights. Firstly, the definition of score function is then employed to objectively obtain the attribute weights based on the CRITIC method. Then, the optimal alternative is chosen through calculating largest relative relational degree from the probabilistic linguistic positive ideal solution (PLPIS) which considers both the largest grey relational coefficient from the PLPIS and the smallest grey relational coefficient form probabilistic linguistic negative ideal solution (PLNIS). This proposed method extends the applications range of the classical GRA method. Finally, a numerical case for site selection of electric vehicle charging stations (EVCS) is employed to illustrate the proposed method. The effectiveness of the proposed method is also verified by some comparative studies.