Nonlinear Deterministic Frontier Model Using Genetic Programming
作者： Chin-Yi Chen , Jih-Jeng Huang , Gwo-Hshiung Tzeng
DOI: 10.1007/978-3-642-02298-2_111
关键词: Function (mathematics) 、 Sample size determination 、 Data envelopment analysis 、 Genetic programming 、 Monte Carlo method 、 Computer science 、 Parametric statistics 、 Regression 、 Symbolic regression 、 Mathematical optimization
摘要: In economics, several parametric regression-based models have been proposed to measure the technical efficiency of decision making units (DMUs). However, problem misspecification restricts use these methods. this paper, symbolic regression is employed obtain approximate optimal production function automatically using genetic programming (GP). Monte Carlo simulation used compare performance data envelopment analysis (DEA), deterministic frontier (DFA) and GP-based DFA with respect three different functions sample sizes. The simulated results indicated that method has better than others nonlinear functions.
nctu.edu.tw
springer.com
harvard.edu参考文章(15)
William H. Greene, The Econometric Approach to Efficiency Analysis The Measurement of Productive Efficiency and Productivity Change. ,(2008) , 10.1093/ACPROF:OSO/9780195183528.003.0002
Flor Castillo, Kenric Marshall, James Green, Arthur Kordon, A methodology for combining symbolic regression and design of experiments to improve empirical model building genetic and evolutionary computation conference. pp. 1975- 1985 ,(2003) , 10.1007/3-540-45110-2_96
John R. Koza, Genetic Programming: On the Programming of Computers by Means of Natural Selection ,(1992)
Shouhong Wang, Nonparametric econometric modelling: A neural network approach European Journal of Operational Research. ,vol. 89, pp. 581- 592 ,(1996) , 10.1016/0377-2217(94)00282-7
W.W. Cooper, K. Tone, Measures of inefficiency in data envelopment analysis and stochastic frontier estimation European Journal of Operational Research. ,vol. 99, pp. 72- 88 ,(1997) , 10.1016/S0377-2217(96)00384-0
John Ruggiero, A new approach for technical efficiency estimation in multiple output production European Journal of Operational Research. ,vol. 111, pp. 369- 380 ,(1998) , 10.1016/S0377-2217(97)00351-2
Konstantinos Giannakas, Kien C. Tran, Vangelis Tzouvelekas, On the choice of functional form in stochastic frontier modeling Empirical Economics. ,vol. 28, pp. 75- 100 ,(2003) , 10.1007/S001810100120
Tser-Yieth Chen, A comparison of chance-constrained DEA and stochastic frontier analysis: bank efficiency in Taiwan Journal of the Operational Research Society. ,vol. 53, pp. 492- 500 ,(2002) , 10.1057/PALGRAVE.JORS.2601318
Shouhong Wang, Adaptive non-parametric efficiency frontier analysis: a neural-network-based model Computers & Operations Research. ,vol. 30, pp. 279- 295 ,(2003) , 10.1016/S0305-0548(01)00095-8
Peter Schmidt, Frontier production functions Econometric Reviews. ,vol. 4, pp. 289- 328 ,(1985) , 10.1080/07474938608800089