A PROBABILISTIC LINGUISTIC VIKOR METHOD TO SOLVE MCDM PROBLEMS WITH INCONSISTENT CRITERIA FOR DIFFERENT ALTERNATIVES

VIKOR is a well-defined multiple criteria decision-making (MCDM) method since it reflects different risk attitudes of decision-makers by measuring the overall performance an alternative under all as “group value” and worst “individual regret”, but cannot deal with MCDM problems where alternatives are inconsistent (different) decision information uncertain. To address these problems, we present probabilistic linguistic combining term sets which portrays uncertain such individual hesitancy incomplete belief flexibly. In addition, introduce aspired tolerable values reference points to measure closeness degrees ideal solution. compare group regrets alternatives, develop vector normalization that considers number criteria. The robustness aggregation results improved based on extended Borda rule, takes into account both ranks in aggregation. A case study personnel evaluation demonstrates effectiveness proposed for solving information.