A nondominated selection procedure with partially consistent non-reciprocal probabilistic linguistic preference relations and its application in social donation channel selection under the COVID-19 outbreaks

摘要

A non-reciprocal fuzzy preference relation (NrFPR) can express partial relations of alterna-tives, including indifference relations, preference relations and incomparability relations, but cannot depict linguistic preference intensities. A probabilistic linguistic preference relation (PLPR) can represent preference intensities in forms of probabilities and linguistic terms, but the incomparability relations of alternatives were not defined in a PLPR. Given that the NrFPR and PLPR can overcome each other's drawbacks, this study proposes the non-reciprocal probabilistic linguistic preference relation (NrPLPR). Six conditions are given to express the partial relations of alternatives. Since the P-cut of probabilistic linguis-tic term sets (PLTSs) is effective in the operations of PLTSs without information loss, we construct the P-cut matrix of an NrPLPR by an adaptive P-determination method. Afterwards, nine rules are provided to define the partially consistent NrPLPR. To repair the inconsistent NrPLPR, a two-stage consistency repairing process, containing the linguis-tic information and probability repairing stages, is introduced. In addition, a non-reciprocal probabilistic linguistic nondominated selection procedure is proposed to rank alternatives. A case study on selecting social donation channels under the COVID-19 outbreaks is given to demonstrate the applicability of the proposed method. A comparative analysis is done to show the effectiveness of the proposed method.