Using Enhanced Russell Model to Solve Inverse Data Envelopment Analysis Problems

This paper studies the inverse data envelopment analysis using the nonradial enhanced Russell model. Necessary and sufficient conditions for inputs/outputs determination are introduced based on Pareto solutions of multiple-objective linear programming. In addition, an approach is investigated to ide...

Full description

Saved in:
Bibliographic Details
Published in:TheScientificWorld 2014-01, Vol.2014 (2014), p.1-10
Main Authors: Ghobadi, S., Rostamy-Malkhalifeh, M., Hosseinzadeh Lotfi, Farhad, Jahanshahloo, G.
Format: Article
Language:English
Subjects:
Data envelopment analysis
Decision making
Efficiency
Functions, Inverse
Linear Models
Linear programming
Mathematical Computing
Mathematical models
Mathematical research
Mathematics - methods
Models, Theoretical
Statistics, Nonparametric
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:This paper studies the inverse data envelopment analysis using the nonradial enhanced Russell model. Necessary and sufficient conditions for inputs/outputs determination are introduced based on Pareto solutions of multiple-objective linear programming. In addition, an approach is investigated to identify extra input/lack output in each of input/output components (maximum/minimum reduction/increase amounts in each a of input/output components). In addition, the following question is addressed: if among a group of DMUs, it is required to increase inputs and outputs to a particular unit and assume that the DMU maintains its current efficiency level with respect to other DMUs, how much should the inputs and outputs of the DMU increase? This question is discussed as inverse data envelopment analysis problems, and a technique is suggested to answer this question. Necessary and sufficient conditions are established by employing Pareto solutions of multiple-objective linear programming as well.
ISSN:2356-6140
1537-744X
1537-744X
DOI:10.1155/2014/571896