Improving the computational complexity and weights dispersion in fuzzy DEA

Saber Saati; Adel Hatami-Marbini

doi:10.1142/9789814417747_0171

Improving the computational complexity and weights dispersion in fuzzy DEA

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

One of the prominent features of standard and fuzzy data envelopment analysis (DEA) is the representation of each of the participating decision making units (DMUs) in the best possible light. This causes two problems; first, the different set of factor weights with large number of zeros and second a large number of linear programming models to solve. In this paper, we propose an efficient method to address these two problems. In proposed method by solving just one linear programming a Common Set of Weights (CSW) is achieved in fuzzy DEA. Since resulted efficiencies by the proposed CSW are interval numbers rather than crisp values, it is more informative for decision maker. The proposed model is applied to a numerical example to demonstrate the concept.

Original language	English
Title of host publication	World Scientific Proceedings Series on Computer Engineering and Information Science 7
Subtitle of host publication	Uncertainty Modeling in Knowledge Engineering and Decision Making: Proceedings of the 10th International FLINS Conference
Editors	Cengiz Kahraman, Etienne E. Kerre, Faik Tunc Bozbura
Publisher	World Scientific Publishing Co. Pte Ltd
Pages	1070-1075
Number of pages	6
Volume	7
ISBN (Electronic)	9789814417754
ISBN (Print)	9789814417730
DOIs	https://doi.org/10.1142/9789814417747_0171
Publication status	Published - 26 Aug 2012
Externally published	Yes
Event	10th International Fuzzy Logic and Intelligent Technologies in Nuclear Science Conference - Istanbul, Turkey Duration: 26 Aug 2012 → 29 Aug 2012 Conference number: 10

Publication series

Name	World Scientific Proceedings Series on Computer Engineering and Information Science
Publisher	World Scientific Publishing Co. Pte Ltd
ISSN (Print)	1793-7868

Conference

Conference	10th International Fuzzy Logic and Intelligent Technologies in Nuclear Science Conference
Abbreviated title	FLINS 2012
Country/Territory	Turkey
City	Istanbul
Period	26/08/12 → 29/08/12

Access to Document

10.1142/9789814417747_0171Licence: Unspecified

Cite this

Saati, S., & Hatami-Marbini, A. (2012). Improving the computational complexity and weights dispersion in fuzzy DEA. In C. Kahraman, E. E. Kerre, & F. T. Bozbura (Eds.), World Scientific Proceedings Series on Computer Engineering and Information Science 7: Uncertainty Modeling in Knowledge Engineering and Decision Making: Proceedings of the 10th International FLINS Conference (Vol. 7, pp. 1070-1075). (World Scientific Proceedings Series on Computer Engineering and Information Science). World Scientific Publishing Co. Pte Ltd. https://doi.org/10.1142/9789814417747_0171

Saati, Saber ; Hatami-Marbini, Adel. / Improving the computational complexity and weights dispersion in fuzzy DEA. World Scientific Proceedings Series on Computer Engineering and Information Science 7: Uncertainty Modeling in Knowledge Engineering and Decision Making: Proceedings of the 10th International FLINS Conference. editor / Cengiz Kahraman ; Etienne E. Kerre ; Faik Tunc Bozbura. Vol. 7 World Scientific Publishing Co. Pte Ltd, 2012. pp. 1070-1075 (World Scientific Proceedings Series on Computer Engineering and Information Science).

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title = "Improving the computational complexity and weights dispersion in fuzzy DEA",

abstract = "One of the prominent features of standard and fuzzy data envelopment analysis (DEA) is the representation of each of the participating decision making units (DMUs) in the best possible light. This causes two problems; first, the different set of factor weights with large number of zeros and second a large number of linear programming models to solve. In this paper, we propose an efficient method to address these two problems. In proposed method by solving just one linear programming a Common Set of Weights (CSW) is achieved in fuzzy DEA. Since resulted efficiencies by the proposed CSW are interval numbers rather than crisp values, it is more informative for decision maker. The proposed model is applied to a numerical example to demonstrate the concept.",

keywords = "Data envelopment analysis (DEA), Decision making units (DMUs), Common Set of Weights (CSW)",

author = "Saber Saati and Adel Hatami-Marbini",

year = "2012",

month = aug,

day = "26",

doi = "10.1142/9789814417747\_0171",

language = "English",

isbn = "9789814417730",

volume = "7",

series = "World Scientific Proceedings Series on Computer Engineering and Information Science",

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editor = "Cengiz Kahraman and Kerre, \{Etienne E.\} and Bozbura, \{Faik Tunc\}",

booktitle = "World Scientific Proceedings Series on Computer Engineering and Information Science 7",

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note = "10th International Fuzzy Logic and Intelligent Technologies in Nuclear Science Conference, FLINS 2012 ; Conference date: 26-08-2012 Through 29-08-2012",

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Saati, S & Hatami-Marbini, A 2012, Improving the computational complexity and weights dispersion in fuzzy DEA. in C Kahraman, EE Kerre & FT Bozbura (eds), World Scientific Proceedings Series on Computer Engineering and Information Science 7: Uncertainty Modeling in Knowledge Engineering and Decision Making: Proceedings of the 10th International FLINS Conference. vol. 7, World Scientific Proceedings Series on Computer Engineering and Information Science, World Scientific Publishing Co. Pte Ltd, pp. 1070-1075, 10th International Fuzzy Logic and Intelligent Technologies in Nuclear Science Conference, Istanbul, Turkey, 26/08/12. https://doi.org/10.1142/9789814417747_0171

Improving the computational complexity and weights dispersion in fuzzy DEA. / Saati, Saber; Hatami-Marbini, Adel.
World Scientific Proceedings Series on Computer Engineering and Information Science 7: Uncertainty Modeling in Knowledge Engineering and Decision Making: Proceedings of the 10th International FLINS Conference. ed. / Cengiz Kahraman; Etienne E. Kerre; Faik Tunc Bozbura. Vol. 7 World Scientific Publishing Co. Pte Ltd, 2012. p. 1070-1075 (World Scientific Proceedings Series on Computer Engineering and Information Science).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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T1 - Improving the computational complexity and weights dispersion in fuzzy DEA

AU - Saati, Saber

AU - Hatami-Marbini, Adel

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PY - 2012/8/26

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N2 - One of the prominent features of standard and fuzzy data envelopment analysis (DEA) is the representation of each of the participating decision making units (DMUs) in the best possible light. This causes two problems; first, the different set of factor weights with large number of zeros and second a large number of linear programming models to solve. In this paper, we propose an efficient method to address these two problems. In proposed method by solving just one linear programming a Common Set of Weights (CSW) is achieved in fuzzy DEA. Since resulted efficiencies by the proposed CSW are interval numbers rather than crisp values, it is more informative for decision maker. The proposed model is applied to a numerical example to demonstrate the concept.

AB - One of the prominent features of standard and fuzzy data envelopment analysis (DEA) is the representation of each of the participating decision making units (DMUs) in the best possible light. This causes two problems; first, the different set of factor weights with large number of zeros and second a large number of linear programming models to solve. In this paper, we propose an efficient method to address these two problems. In proposed method by solving just one linear programming a Common Set of Weights (CSW) is achieved in fuzzy DEA. Since resulted efficiencies by the proposed CSW are interval numbers rather than crisp values, it is more informative for decision maker. The proposed model is applied to a numerical example to demonstrate the concept.

KW - Data envelopment analysis (DEA)

KW - Decision making units (DMUs)

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A2 - Kahraman, Cengiz

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Saati S, Hatami-Marbini A. Improving the computational complexity and weights dispersion in fuzzy DEA. In Kahraman C, Kerre EE, Bozbura FT, editors, World Scientific Proceedings Series on Computer Engineering and Information Science 7: Uncertainty Modeling in Knowledge Engineering and Decision Making: Proceedings of the 10th International FLINS Conference. Vol. 7. World Scientific Publishing Co. Pte Ltd. 2012. p. 1070-1075. (World Scientific Proceedings Series on Computer Engineering and Information Science). doi: 10.1142/9789814417747_0171

Improving the computational complexity and weights dispersion in fuzzy DEA

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