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     Research Journal of Applied Sciences, Engineering and Technology


Production Possibility of Production Plans in DEA with Imprecise Input and Output

1Hadi Bagherzadeh Valami, 2Reza Raei Nojehdehi, 2Pantea Maleki Moghadam Abianeh and 3Hesam Zaeri
1Department of Applied Mathematics, Shahr-e-ReyBranch, Islamic Azad University, Tehran, Iran
2Department of Industrial Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran
3Department of Information Technology, Adiban University, Garmsar Iran
Research Journal of Applied Sciences, Engineering and Technology  2013  17:4264-4267
http://dx.doi.org/10.19026/rjaset.5.4414  |  © The Author(s) 2013
Received: July 07, 2012  |  Accepted: August 15, 2012  |  Published: May 01, 2013

Abstract

Data Envelopment Analysis (DEA) is a mathematical approach to evaluate the relative efficiency of Decision Making Units (DMUs). DEA models create an efficient frontier using the best observed data. This frontier bounds all feasible production plans named Production Possibility Set. Traditional DEA models require crisp input and output data, but in many situations the data are not precisely available. When the data of the DMUs are imprecise, the location of the efficient frontier cannot be determined precisely therefore the boundary of the production possibility set is imprecise. This paper assumes that some of the data are in the interval format available and then considers the production possibility set as a fuzzy set that all the production plans belong to this set with different degrees of membership and a membership function for the production plans related to the fuzzy production possibility set is derived under a geometrical approach.

Keywords:

Data envelopment analysis, fuzzy set, production possibility set,


References


Competing interests

The authors have no competing interests.

Open Access Policy

This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Copyright

The authors have no competing interests.

ISSN (Online):  2040-7467
ISSN (Print):   2040-7459
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