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...

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 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 method for ranking decision making units (dmus) using some of the multiple criteria decision making / multiple attribute decision making          (mcdm /madm) techniques, namely, interval analytic hierarchy process (iahp)          and the technique for order preference by similarity to an ideal solution (topsis).          since the efficiency score of unity is assigned to ...

<span lang="EN-US">Planning production is an essential component of the decision-making process, which has a direct bearing on effectiveness systems. This study’s objective to investigate efficiency performance units (DMU) in relation planning issues. However, system manufacturing environment frequently subject uncertain situations, such as demand and labor, this can have effect not only ...

Performance measurement in the presence of fixed-sum outputs in data envelopment analysis (DEA) is an interesting and most frequently studied subject in the field of operations research. Different definitions of relative efficiency in the presence of fixed-sum outputs have been proposed in the literature of data envelopment analysis and in all of the existing definitions a common equilibrium ef...

Introduction: Data envelopment analysis (DEA) is a data-oriented method for measuring and benchmarking the relative efficiency of peer decision making units (DMUs) with multiple inputs and multiple outputs. DEA was initiated in 1978 when Charnes, Cooper and Rhodes (CCR) demonstrated how to change a fractional linear measure of efficiency into a linear programming format. This non-parametric app...

Data envelopment analysis (DEA) is a method for estimating efficiency of decision making units (DMU).The method done by means of weighted output to input ratio with the weights being optimal virtual prices of such activities for all units. Cross efficiency evaluation has long been proposed as an alternative method for ranking DMUs. The major problem that reduced the usefulness of cross efficien...

Data Envelopment Analysis (DEA) is a powerful quantitative tool that provides a means to obtain useful information about efficiency and performance of firms, organizations, and all sorts of functionally similar, relatively autonomous operating units, known as Decision Making Units (DMU). Usually the investigated DMUs are characterized by a vector of multiple inputs and multiple outputs. Unfortu...

this paper presents a data envelopment analysis (dea) model combined with bootstrapping to assess performance of one of the data mining algorithms. we applied a two-step process for performance productivity analysis of insurance branches within a case study. first, using a dea model, the study analyzes the productivity of eighteen decision-making units (dmus). using a malmquist index, dea deter...