A novel hybrid approach based on fuzzy DEA-AHP

Abstract

The data envelopment analysis (DEA) model is a non-parametric programming technique that helps to efficiency evaluating for every decision making units (DMUs) with multiple inputs and multiple outputs. In traditional DEA model, we need crisp data. But in the real world, most of the data are imprecise and uncertain. A major cause of uncertainty related to the non-quantifiable, incomplete and unachievable information. For this reason, fuzzy logic and fuzzy sets developed in different models of DEA. In this paper, a new hybrid model is developed for performance evaluation problems ranking of DMUs, with multiple inputs and fuzzy outputs. To achieve the best ranking of DMUs, fuzzy analytical hierarchy process (FAHP) is applied. Solving FAHP ends up in a full ranking of DMUs. Finally, to illustrate the proposed model an example is presented.