Choquet-Integral-Based Data Envelopment Analysis with Stochastic Multicriteria Acceptability Analysis

Data envelopment analysis (DEA) is a non-parametric method for measuring the efficiencies of decision-making units (DMUs) by using set inputs and outputs. However, traditional DEA models always assume that or outputs are independent each other, which unrealistic in practical problems. To reflect interactions between outputs, Choquet integral employed models. The usually used to find some specific input output weights DMUs optimize efficiency score DMUs, but corresponding optimal DMU may not be distributed symmetrically, say, space different DMUs. Instead finding self-efficiency cross-efficiency based on weights, stochastic multicriteria acceptability explore evaluation weight calculate Choquet-integral-based indices proposed considers can make more efficient also measure become an one exploring supporting information space. Examples given illustrate method.