If a DEA model has a mix of categorical and continuous variables a standard LP formulation can still be used by entering all combinations of categorical and continuous variables as different types of inputs and/or outputs. Most units will then not have positive levels of all variables. The implications for selection of peers are investigated. Peers can have the same or fewer types of inputs tha...

in order to perform each component of agricultural practices, its plan should be rationalized economically and technically. in a study for recognition patterns of energy inputs and outputs in saffron fields of southern khorasan, iran, during a five years exploitation period, two questionnaires were prepared, one for the first cultivation year, and another for crop management and harvest during ...

this research identifies returns to scale (rts) of efficient decision making units (dmus) with desirable (good) and undesirable (bad) inputs and outputs by presenting a new dea (data envelopment analysis) approach. in this study, we first introduce a new input-output oriented model to determine efficient dmus in the presence of undesirable factors and then, returns to scale of these dmus are es...

The production possibility set (PPS) is defined as the set of all inputs and outputs of a system in which inputs can produce outputs. In data envelopment analysis (DEA), identification of the strong defining hyperplanes of the empirical production possibility set (PPS) is important, because they can be used for determining rates of change of outputs with change in inputs. Also, efficient hyperp...

This paper investigates a new class of linear multi-agent network systems, in which nodes are coupled by dynamic edges in the sense that each edge has a dynamic system attached as well. The outputs of the edge dynamic systems form the external inputs of the node dynamic systems, which are termed “neighboring inputs” representing the coupling actions between nodes. The outputs of the node dynami...

The basic assumption in data envelopment analysis patterns (DEA) (such as the CCR andBCC models) is that the value of data related to the inputs and outputs is a precise andpositive number, but most of the time in real conditions of business, determining precisenumerical value is not possible in for some inputs or outputs. For this purpose, differentmodels have been proposed in DEA for imprecis...

Data Envelopment Analysis (DEA) has been long employed as a popular methodology to evaluate the performance of various production activities with multiple inputs and outputs. However, an important issue is that the production process in the real world inevitably generates undesirable outputs (like wastes and pollutants) along with desirable outputs. Therefore, the undesirable outputs should be ...

Data envelopment analysis (DEA) is non-parametric linear programming (LP) based technique for estimating the relative efficiency of different decision making units (DMUs) assessing the homogeneous type of multiple-inputs and multiple-outputs. The procedure does not require a priori knowledge of weights, while the main concern of this non-parametric technique is to estimate the optimal weights o...

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...