DEA Problems under Geometrical or Probability Uncertainties of Sample Data

Althaler, Karl S. and Slavova, Tatjana (October 2000) DEA Problems under Geometrical or Probability Uncertainties of Sample Data. IHS Economics Series 89

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Abstract or Table of Contents

Abstract: This paper discusses the theoretical and practical aspects of new methods for solving DEA problems under real-life geometrical uncertainty and probability uncertainty of sample data. The proposed minimax approach to solve problems with geometrical uncertainty of sample data involves an implementation of linear programming or minimax optimization, whereas the problems with probability uncertainty of sample data are solved through implementing of econometric and new stochastic optimization methods, using the stochastic frontier functions estimation.;

Item Type: IHS Series
Keywords: 'DEA' 'Ungewissheit von Daten' 'Lineare Programmierung' 'Minimax-Optimierung' 'Stochastische Optimierungsmethoden' 'Stochastische Grenzfunktionen' 'Sample data uncertainty' 'Linear programming' 'Minimax optimization' 'Stochastic optimization' 'Stochastic frontier functions'
Classification Codes (e.g. JEL): C81, D81, H72
Status: Published
Date Deposited: 26 Sep 2014 10:37
Last Modified: 07 Apr 2016 09:35
URI: http://irihs.ihs.ac.at/id/eprint/1295

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