Applied Mathematical Sciences, Vol. 7, 2013, no. 28, 1387 - 1392 HIKARI Ltd, www.m-hikari.com Evaluation of Decision Making Units in the Presence of Fuzzy and Non-discretionary Neda Fathi and Mohammad Izadikhah Department of Mathematics, Arak Branch, Islamic Azad University, Arak, Iran nedafathi112@yahoo.com, m-izadikhah@iau-arak.ac.ir Copyright © 2013 Neda Fathi and Mohammad Izadikhah. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Abstract In original data envelopment analysis (DEA) models, input and output are measured by exact values on a ratio scale. However, this assumption may not be always valid. For example some data may be only known as in forms of fuzzy and non–discretionary data. In this paper we try to suggest a generalized model when some inputs and outputs are fuzzy and non-discretionary data. Keywords: Data envelopment analysis, fuzzy data, non-discretionary data. 1. Introduction Data envelopment analysis (DEA),is currently a popular technique for analyzing technical efficiency. DEA originally proposed by Charnes et al.[1]is a non-parametric technique for measuring and evaluating the relative efficiencies of a set of entities, called decision making units (DMUs),with the common inputs and outputs. Often the assumption of homogeneous environments is violated and factors that describe the differences in the environments need to be including in the analysis. These factors, and other factors outside the control of the DMUs, are frequently called non- discretionary factors instances from the DEA literature include snowfall or weather in evaluating the efficiency of maintenance units. Therefore, some papers were presented on the theorical development of this technique with non-discretionary data. Many researchers addressed the problem with non-discretionary data (Banker and