determination of trade-off, which they are feasible and similar variations on all of decision making units (dmu), is important issue in data envelopment analysis (dea). in this paper, we select these trade-offs based on an external evaluation of dmus such that the correlation between external evaluation and technical evaluation resulted from dea model is maximized. in fact, we sift the trade-of...

Data Envelopment Analysis (DEA) is a non-parametric technique which is based on mathematical programming for evaluating the efficiency of a set of Decision Making Units (DMUs). Throughout applications, managers encounter with stochastic data and the necessity of having a method that is able to evaluate efficiency and rank efficient units has been under consideration. In this paper considering t...

This paper addresses several mechanisms for overall ranking Decision Making Units (DMUs) according to the contribution of DMUs relative efficiency score a merger considering aggregate units The possible organization agents outside each naturally influences score, which motivates use games in partition function form and specific indices based on Shapley value. Several computational problems aris...

Data Envelopment Analysis (DEA) is a widely used non-parametric method for ranking by Decision-Making Units (DMU). Despite the fact that DEA method does not require numerous preconditions, the necessity of the DMUs to be homogeneous is one of the most important rules in applying this technique. Moreover, in real world problems, due to the nature of DMUs, the need for ranking the grouped data ha...

Data Envelopment Analysis (DEA) is an approach based on linear programming to assess the relative efficiency of peer Decision Making Units (DMUs). Typically, each DMU is free to choose the weights of the factors used in its evaluation. However, the evaluator’s preferences may not warrant so much freedom. Several approaches have been proposed to allow the incorporation of managerial preferences ...

The motivation of this paper is to propose such equitable method for ranking all decision making units (DMUs) in dynamic Data Envelopment Analysis (DDEA) framework. As far as we are aware there is not more studies in dynamic DEA literature. What's more, in such cases the best operating unit is important to be sampled for the others in under evaluated time periods. However, in this special conce...

Abstract In this paper, by using Data Envelopment Analysis (DEA) technique a method is proposed to find efficient solutions of 0-1 Multiple Objective Linear Programming (MOLP) problem. In this method from a feasible solution of 0-1 MOLP problem, a Decision Making Unit (DMU) without input vector is constructed in which output vector for DMU is the values of objective functions. The method consis...

Data envelopment analysis (DEA) is a method for measuring the relative efficiencies of a set of decision-making units (DMUs) that use multiple inputs to produce multiple outputs. In this paper, we study the measurement of DMU performances in DEA in situations where input and/or output values are given as imprecise data. By imprecise data we mean situations where we only know that the actual val...

This paper proposes a new method based on the ideal input vector to estimate inputs of a given decision making unit (DMU) when some or all of its outputs are increased to maintain its current efficiency level. In other words, this paper studied the following question: How much would be the increase in the inputs of the DMU if the decision maker increases certain outputs to a particular unit in ...