Data envelopment analysis model with decision makers’ preferences: a robust credibility approach

Data envelopment analysis (DEA) is one of the widely used methods to measure efficiency scores decision making units (DMUs). Conventional DEA unable consider both uncertainty in data and makers’ (DMs) judgments evaluations. This study, address shortcomings conventional DEA, proposes a new best worst method (BWM)- robust credibility (BWM-RCDEA) model estimate DMUs considering DMs’ preferences uncertain data, simultaneously. First, handle input output variables, fuzzy has been applied. Additionally, constructing sets modeled using optimization with perturbation degree. In this paper, two types RCDEA models are proposed: exact inputs outputs outputs. addition, deal flexibility weights incorporating judgement into model, bi-objective BWM-RCDEA introduced. Finally, proposed solved min–max approach. To illustrate usefulness capability 39 distribution companies Iran investigated results analyzed discussed. based on results, recommendations have made for policy makers.