An improved approach to find and rank BCC-efficient DMUs in data envelopment analysis (DEA)

Authors

  • Morteza Rahmani Technology Development Institute (ACECR), Sharif branch, Tehran, Iran
Abstract:

Recently, a mixed integer data envelopment analysis (DEA) model has been proposed to find the most BCC-efficient (or the best) decision making unit (DMU) by Toloo (2012). This paper shows that the model may be infeasible in some cases, and when the model is feasible, it may fail to identify the most efficient DMU, correctly. We develop an improved model to find the most BCC-efficient DMU that removes the mentioned drawbacks. Also, an algorithm is proposed to find and rank other most BCC-efficient DMUs, when there exist more than one BCC-efficient DMUs. The capability and usefulness of the proposed model are indicated, using a real data set of nineteen facility layout designs (FLDs) and twelve flexible manufacturing systems (FMSs).

Upgrade to premium to download articles

Sign up to access the full text

Already have an account?login

similar resources

An approach to rank efficient DMUs in DEA based on combining Manhattan and infinity norms

In many applications, discrimination among decision making units (DMUs) is a problematic technical task procedure to decision makers in data envelopment analysis (DEA). The DEA models unable to discriminate between extremely efficient DMUs. Hence, there is a growing interest in improving discrimination power in DEA yet. The aim of this paper is ranking extreme efficient DMUs in DEA based on exp...

full text

A New Method in Data Envelopment Analysis to Find Efficient Decision Making Units and Rank both Technical Efficient and Inefficient DMUs together

The inefficient DMUs are usually arranged after the technical efficient ones by DEA methods, however, it is possible that a technical efficient DMU neither be efficient nor be more efficient than some inefficient ones. This study distinguishes between the terms ‘technical efficiency’ and ‘efficiency’ and demonstrates that the technical efficiency is a necessary condition for being efficient and...

full text

Data Envelopment Analysis with Nonhomogeneous DMUs

Data envelopment analysis (DEA), as originally proposed, is a methodology for evaluating the relative efficiencies of a set of homogeneous decision-making units (DMUs) in the sense that each uses the same input and output measures (in varying amounts from one DMU to another). In some situations, however, the assumption of homogeneity among DMUs may not apply. As an example, consider the case wh...

full text

Data envelopment analysis with missing values: An interval DEA approach

Missing values in inputs, outputs cannot be handled by the original data envelopment analysis (DEA) models. In this paper we introduce an approach based on interval DEA that allows the evaluation of the units with missing values along with the other units with available crisp data. The missing values are replaced by intervals in which the unknown values are likely to belong. The constant bounds...

full text

returns to scale of dmus by interval inputs and outputs in data envelopment analysis (dea)

the basic models of data envelopment analysis (dea) are designed in such a way that the values of input and output indicators should be identified and known in them. in other words, these models are not used to consider inaccurate, interval, fuzzy, judgment data. in this paper, the aim is to not only review the past researches about the efficiency of the units by interval data and represent the...

full text

My Resources

Save resource for easier access later

Save to my library Already added to my library

{@ msg_add @}


Journal title

volume 10  issue 2

pages  25- 34

publication date 2017-06-30

By following a journal you will be notified via email when a new issue of this journal is published.

Hosted on Doprax cloud platform doprax.com

copyright © 2015-2023