Arbeitspapier
Smoothing the frontier in the DEA models
Some inadequate results may appear in the DEA models as in any other mathematical model. In the DEA scientific literature several methods were proposed to deal with these difficulties. In our previous paper, we introduced the notion of terminal units. It was also substantiated that only terminal units form necessary and sufficient sets of units for smoothing the frontier. Moreover, some relationships were established between terminal units and other sets of units that were proposed for improving the frontier. In this paper we develop a general algorithm for smoothing the frontier. The construction of algorithm is based on the notion of terminal units. Our theoretical results are verified by computational results using real-life data sets and also confirmed by graphical examples.
- Sprache
-
Englisch
- Erschienen in
-
Series: Memorandum ; No. 11/2016
- Klassifikation
-
Wirtschaft
Operations Research; Statistical Decision Theory
Optimization Techniques; Programming Models; Dynamic Analysis
Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity
- Thema
-
Data Envelopment Analysis (DEA)
Terminal units
Anchor units
Exterior units
- Ereignis
-
Geistige Schöpfung
- (wer)
-
Krivonozhko, Vladimir W.
Førsund, Finn R.
Lychev, Andrey V.
- Ereignis
-
Veröffentlichung
- (wer)
-
University of Oslo, Department of Economics
- (wo)
-
Oslo
- (wann)
-
2016
- Handle
- Letzte Aktualisierung
-
10.03.2025, 11:43 MEZ
Datenpartner
Dieses Objekt wird bereitgestellt von:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Objekttyp
- Arbeitspapier
Beteiligte
- Krivonozhko, Vladimir W.
- Førsund, Finn R.
- Lychev, Andrey V.
- University of Oslo, Department of Economics
Entstanden
- 2016
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