Efficiency analysis with interval-scale data based on separating hyperplane of decision making units
نویسنده
چکیده
The traditional data envelopment analysis (DEA) model can evaluate the relative efficiencies of a set of decision making units (DMUs) with ratio scale inputs and outputs, but it cannot handle interval scale data. This study develop an approach to efficiency analysis to deal with both interval-scale data and ratio scale data. This approach introduces a measure of inefficiency and identifies efficient units as is done in DEA models with VRS technology. The basic idea in the approach is to obtain a separating hyperplane of DMUs so that the hyperplane can separate the maximum number of DMUs whose performances are not better than a DMU under evaluation, from the rest of the DMUs. Performance measure is defined as a ratio of not-better units to all units. Also, this paper presents a relationship between the performance measures with those in DEA models with VRS technology.
منابع مشابه
Efficiency Analysis Based on Separating Hyperplanes for Improving Discrimination among DMUs
Data envelopment analysis (DEA) is a non-parametric method for evaluating the relative technical efficiency for each member of a set of peer decision making units (DMUs) with multiple inputs and multiple outputs. The original DEA models use positive input and output variables that are measured on a ratio scale, but these models do not apply to the variables in which interval scale data can appe...
متن کاملThe Efficiency of MSBM Model with Imprecise Data (Interval)
Data Envelopment Analysis (DEA) is a mathematical programming-based approach for evaluates the relative efficiency of a set of DMUs (Decision Making Units). The relative efficiency of a DMU is the result of comparing the inputs and outputs of the DMU and those of other DMUs in the PPS (Production Possibility Set). Also, in Data Envelopment Analysis various models have been developed in order to...
متن کاملMeasuring the overall performances of decision-making units in the presence of imprecise data
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...
متن کاملComputing the efficiency interval of decision making units (DMUs) having interval inputs and outputs with the presence of negative data
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...
متن کامل