Target setting in data envelopment analysis using MOLP

A Value Efficiency-Based Target Setting Approach in Data Envelopment Analysis

Basic models of Data Envelopment Analysis are intrinsically preference-free, in the sense that they consider all inputs and outputs and also all decision making units of the same importance. Although this property is beneficial in many ways, it has some drawbacks simultaneously, as the decision makers’ preferences are not taken into account in the process of evaluating units.  To overcome this ...

Efficient location by using data envelopment analysis

So far, many types of location models have been developed to find optimal spatial patterns according to different spatial metrics such as cost, coverage and availability.  The initial focus of these models is on the location availability of service providers and demand estimates, and some of these models are within the framework of multi-objective programming models.  After the advent of scienc...

Target setting in additive models with preferences and interval data

The selection of a single and acceptable target in Data Envelopment Analysis

There are several systems in real situations that only accept a single and acceptable benchmark for efficiency improvement. For instance, when we are going to select a target for a country, the target country should be as close as the view of culture, economics and politics to the inefficient country. Otherwise, it would not be acceptable. Therefore, an inefficient country for several reaso...

A Non-radial Approach for Setting Integer-valued Targets in Data Envelopment Analysis

Data Envelopment Analysis (DEA) has been widely studied in the literature since its inception with Charnes, Cooper and Rhodes work in 1978. The methodology behind the classical DEA method is to determine how much improvements in the outputs (inputs) dimensions is necessary in order to render them efficient. One of the underlying assumptions of this methodology is that the units consume and prod...