Gap minimization for peer-evaluation in DEA cross-efficiency

Cross-efficiency evaluation is an effective and widely used method for ranking decision making units (dmus) in data envelopment analysis (dea). gap minimization criterion is introduced in aggressive and benevolent cross-efficiency methods to avoid possible extreme efficiency from peer-evaluation and to get equitable results. on the basis of this criterion,a weighted cross-efficiency method with similarity distance that,respectively,considers the aggressive and the benevolent formulations is proposed to determine cross-efficiency. the weights of the cross-evaluation determined by this method are positively influenced by self-evaluation and thus are propitious to resolving conflict. numerical demonstration reveals the feasibility of the proposed method. © 2014 anrong yang et al.