data envelopment analysis (dea) is a mathematical programming method in operations research that can be used to distinguish between efficient and inefficient decision making units (dmus). however, the conventional dea models do not have the ability to rank the efficient dmus. this article suggests bootstrapping method for ranking measures of technical efficiency as calculated via non-radial mod...

The proposed bi-objective fuzzy data envelopment analysis (BOFDEA) model is a new approach to assess the performance efficiency of decision-making units (DMUs) in uncertain environments using α-cuts. based on (FDEA) and considers two objectives, solution method ranking system are provided. Generally, score obtained for DMU α-cut an interval. Intervals partially ordered sets, due which intervals...

China’s urbanization over the past thirty years has been fastest in history and led to significant challenges balancing energy use. As a result, this study proposed comprehensive green assessment index system considering use environment protection together. To be specific, principal component analysis was applied eliminate redundant information, slacks-based measure model used evaluate efficien...

in this paper, a new revenue efficiency data envelopment analysis (re-dea) approach is considered for finding the most revenue efficient unit with price uncertainty in both optimistic and pessimistic perspectives. the optimistic and pessimistic perspectives use efficient frontier and inefficient frontier, respectively. an integrated model is introduced to find decision making units (dmus) that ...

this study uses the data envelopment analysis (dea) to assess the progress/regression of decision-making units (dmus) having a two-stage structure‎. ‎the progress/regression of these dmu can be assessed in the first stage‎, ‎the second stage‎, ‎and the whole system‎. ‎in the first stage‎, ‎the progress/regression of bank branches in collecting resources and in the second stage their progress/re...

data envelopment analysis (dea) as a non-parametric method for efficiency measurement allows decision making units (dmus) to select the most advantageous weight factors in order to maximize their efficiency scores.  in most practical applications of dea presented in the literature, the presented models assume that all inputs are fully desirable. however, in many real situations undesirable inpu...

this paper proposes a new approach for determining efficient dmus in dea models using inverse optimi-zation and without solving any lps. it is shown that how a two-phase algorithm can be applied to detect effi-cient dmus. it is important to compare computational performance of solving the simultaneous linear equa-tions with that of the lp, when computational issues and complexity analysis are a...

data envelopment analysis (dea) is a non-parametric method for assessing relative efficiency of decision-making units (dmus). every single decision-maker with the use of inputs produces outputs. these decision-making units will be defined by the production possibility set. resource allocation to dmus is one of the concerns of managers since managers can employ the results of this process to all...

Data envelopment analysis (DEA) is a method to evaluate the relative efficiency of decision making units (DMUs). In this method, the issue has always been to determine a set of weights for each DMU which often caused many problems. Since the DEA models also have the multi-objective linear programming (MOLP) problems nature, a rational relationship can be established between MOLP and DEA problem...

  Data envelopment analysis (DEA) is a nonparametric approach to evaluate theefficiency of decision making units (DMU) using mathematical programmingtechniques. Almost, all of the previous researches in stochastic DEA have been usedthe stochastic data when the inputs and outputs are normally distributed. But, thisassumption may not be true in practice. Therefore, using a normal distribution wi...