resource allocation and optimal leveling are among the top challenges in project management. this paper presents a dea-based procedure for determining an optimal level of inputs to produce a fixed level of outputs. to achieve this goal, we assume that the levels of outputs can be forecasted in the next season and the procedure will determine optimal level of inputs for all dmus. such as some of...

One of the major problems in Data Envelopment Analysis (DEA) is to determine the projection of inefficient Decision Making Units (DMUs) into the efficient frontier. In conventional DEA models, inputs and outputs of inefficient DMUs alter arbitrarily for reaching to the efficient frontier. Nevertheless, sometimes the ability of DMUs is defined and restricted. Moreover, there are situations in th...

Data Envelopment Analysis (DEA) is a method for measuring the efficiency of peer decision making units (DMUs) with multiple inputs and outputs. The traditional DEA treats decision making units under evaluation as black boxes and calculates their efficiencies with first inputs and last outputs. This carries the notion of missing some intermediate measures in the process of changing the inputs to...

One of the issues in Data Envelopment Analysis (DEA) is sensitivity and stability region of the speci c decision making unit (DMU), included ecient and inecient DMUs. In sensitivity analysis of ecient DMUs,the largest region should be found namely stability region thatdata variations are only for ecient DMU under evaluation and the data for the remainingDMUs are assumed xed. Also ecient DMU u...

since data envelopment analysis (dea) introduced in 1970s, it has been widely applied to measure the efficiency of a wide variety of production and operation systems. recently dea has been extended to examine the efficiency of decision making units (dmus) with two-stage network structures or processes, where the outputs from the first stage are intermediate measures that make up the inputs of t...

In this current study a generalized super-efficiency model is first proposed for ranking extreme efficient decision making units (DMUs) in stochastic data envelopment analysis (DEA) and then, a deterministic (crisp) equivalent form of the stochastic generalized super-efficiency model is presented. It is shown that this deterministic model can be converted to a quadratic programming model. So fa...