DMU efficiency assessment using data envelopment analysis in fuzzy environment

Authors

  • Harizmar Izquierdo Madrid Universidad Centroccidental Lisandro Alvarado, Venezuela
  • Belkis López de Lameda Universidad Centroccidental Lisandro Alvarado, Venezuela
  • Maria Elena Torres Samuel Universidad Centroccidental Lisandro Alvarado, Venezuela
  • Ennodio Torres Cruz Universidad Centroccidental Lisandro Alvarado, Venezuela

Keywords:

Efficiency, data envelopment analysis, fuzzy environment

Abstract

The objective of this paper is to develop a method based on fuzzy logic for the evaluation of the efficiency of decision units (Decision Making Unit, DMU) using Data Envelopment Analysis (DEA) for the handling of inaccurate data. The Alpha-cut approach is used for efficiency assessment, and the obtained fuzzy parameters are then sorted. For the evaluation of the method's usefulness, the data of a Hospital system and 12 DMU's were used. This research proposes an approach for the valuation and classification of DMU's, useful for the decision making process.

Downloads

Download data is not yet available.

References

F. Chediak y L. Valencia. Metodología de medición de eficiencia mediante la técnica de análisis envolvente de datos. Vector, 5(Enero -Diciembre):70-81, 2008.

H. Gutiérrez. Calidad y Productividad, Cuarta Edición. McGraw Hill, 2014.

G. Barrios. La medición de la eficiencia técnica mediante el análisis envolvente de datos. http://www.eumed.net/ce/2007c/gybc-a.htm, 2008.

A. Charnes, W. Cooper y E. Rhodes. Measuring the efficiency of decision making units. European Journal of Operational Research, 2(6):429-444, 1978.

A. F. Da Silva, R. de Carvalho Miranda y F. A. Silva Marins. Um modelo fuzzy-dea-game para estratégias de produção sob incerteza. Rev. adm.empres, 55(1):78-94, 2015.

R. Bellman y L. Zadeh. Decision-making in a fuzzy environment. Management Science, 17 B(4):141-164, 1970.

L. Canós, E. Casasús, T. Lara, V. Lara y J. C. Pérez. Un algoritmo fuzzy para la selección de personal basado en agregación de competencias. X Jornadas de ASEPUMA y III Encuentro Internacional, 2007.

D. Aigner, C. A. Knox Lovell y P. Schmidt. Formulation and estimation of stochastic frontier production function models. Journal of Econometrics,6(1):21-37, 1977.

W. Meeusen y J. Van Den Broeck. Efficiency estimation from Cobb-Douglas production functions with composed error. International Economic Review, 18(2):435-444, 1977.

M. Farrell. The measurement of productive efficiency. Journal of Royal Statistical Society, 120(3):253-281, 1957.

R. Banker, A Charnes y W. Cooper. Some models for estimating technical and scale efficiencies in Data Envelopment Analysis. Managenent Science, 30(9):1078-1092, 1984.

P. Rotela, E. de Oliveira, A. da Silva, F. Riera, V. de Mello y L. A. de Carvalho. Data envelopment Analysis and Fuzzy Theory: Efficiency Evaluation under uncertainty in portfolio optimization. Wseas Transactions on Business and Economics, 12(4):74-8, 2015.

S. Medina y O. Manco. Diseño de un sistema experto difuso: evaluación de riesgo crediticio en firmas comisionistas de bolsa para el otorgamiento de recursos financieros. Estudios Gerenciales, 23(104):101-129, 2007.

F. Castiblanco. La incertidumbre y la subjetividad en la toma de decisiones: una revisión desde la lógica difusa. Revista latinoamericana de pensamiento, teoría e investigación contable. LÚMINA, 14:116-140, 2013.

R. Pascual. Técnicas de análisis económico aplicado ii. bloque iii (curso 2011-2012). GITETUR. Grupo para la Investigación Tecnológica en Economía en Turismo. http://hdl.handle.net/10045/19658, 2011.

C. Kao y S. T. Liu. Fuzzy efficiency measures in Data Envelopment Analysis. Fuzzy Sets and Systems, 103(3):427-437, 2000.

P. Guo y Tanaka H. Fuzzy DEA: A perceptual evaluation method. Fuzzy Sets and Systems, 119(1):149-160, 2001.

O. B. Olesen y N. C. Petersen. Chance Constrained Efficiency Evaluation. Management Science, 41(3):442-457, 1995.

M. Pla Ferrando. Modelos flexibles para la valoración de la eficiencia. Tesis Doctoral. Universidad Politécnica de Valencia. España, 2013.

A. Hatami-Marbini, A. Emrouznejad y M. Tavana. A Taxonomy and Review of the fuzzy data Envelopment Analysis Literature, Two Decades in the Making. European Journal of Operational Research, 21(3):475-472, 2011.

M. A. Tubón Amán. Lógica borrosa y análisis de las Finanzas en el Sector Cooperativo. Proyecto de investigación, previo a la obtención del Título de Ingeníera en Contabilidad y Auditoría. Universidad Técnica de Ambato, Facultad de Contabilidad y Auditoría, 2016.

C. Kahraman y E. Tolga. Data envelopment analysis using Fuzzy concept. In Proceedings of the The 28th International Symposium on Multiple- Valued Logic (ISMVL '98), pages 338-343, 1998.

J. K. Sengupta. A Fuzzy systems approach in data envelopment analysis. Comput. Math. Applic, 24(8-9):259-266, 2011.

K. Triantis y O. Girod. A mathematical programming approach for measuring technical efficiency in a fuzzy environment. J. Prod. Anal, 10(1):85-102, 1998.

S. Lertworasirikul, S. Fang, J. Joines y H. Nuttle. Fuzzy data envelopment analysis (DEA): a possibility approach. Fuzzy Sets and Systems, 139(2):379-394, 2003.

A. Hatami-Marbini S. Saati y A. Makui. Ideal and anti-ideal decision making units: a Fuzzy DEA approach. Journal of Industrial Engineering International, 5(10):31-41, 2010.

F. S Bittencourt de Lemos, A. Fiorese, O. C. Alves Junior y R. G. Vieira. Using Data Envelopment Analysis and Fuzzy Logic as Intelligent Risk-Based Decision Making Support for Virtual Organizations. Journal of Industrial Engineering International: In C. Kahraman and S. Cevik Onar (eds.): Intelligent Techniques in Engineering Management. Theory and Applications. Springer International Publishing Switzerland, 2015.

S Bray, L. Caggiani y M. Ottomanelli. Measuring transport systems efficiency under uncertainty by fuzzy sets theory based Data Envelopment Analysis: theoretical and practical comparison with traditional DEA model. Transportation Research Procedia, 5:186-200, 2015.

R. P. Sreedevi, V. Vimala, P. Rameswari y S. Sateesh. An Aplication of Fuzzy Logic and DEA in Agriculture Sector. International Journal of Engineering Science, 6(5):4876- 4878, 2016.

M. Salari y H. Khamooshi. A better project performance prediction model using fuzzy time series and Data Envelopment Analysis. Journal of the Operational Research Society, page 1-14, 2016.

P. Wanke, C. P Barros y O. R. Nwaogbe. Assessing productive efficiency in nigerian airports using fuzzy-dea. Transport Policy, 49:9-19, 2016.

A. Esmaeili y M. Sadegh Horri. Efficiency evaluation of customer satisfaction index in e-banking using the fuzzy data envelopment analysis. Management Science Letters, 4(1):71-86, 2014.

M. Sadiq y S. K. Jain. Applying fuzzy preference relation for requirements prioritization in goal oriented requirements elicitation process. International Journal of System Assurance Engineering y Managemen, 5(4):711-723, 2014.

B. Aouni, J. M. Martel y A. Hassain. Fuzzy goal programming model: an overview of the current state-of-the-art. Journal of Multi-Criteria Decision Analysis, 16(5-6):149-161, 2009.

A. Kaufmann. Introduction to the Theory of Fuzzy Subsets. Vol. 1. IEEE Transactions on Systems, Man, and Cybernetic, 7(6):495-496, 1977.

C. Kao, C. C. Liy S. P. Chen. Parametric programming to the analysis of fuzzy queues. Fuzzy Sets and Systems, 107(1):93-10, 1999.

R. A. Yager. Characterization of the extension principle. Fuzzy Sets and Systems, 18(3):205-217, 1986.

L. A. Zadeh. Outline of a new approach to the analysis of complex systems and decision processes. IEEE Trans. Systems Man Cybernet, 3(1):28-44, 1973.

H. J. Zimmermann. Fuzzy Set Theory and its Applications. Second edition. Kluwer-Nijho Publisher, 1991.

C. Chen y C. Klein. An efficient approach to solving fuzzy MADM problems. Fuzzy Sets and Systems, 88(1):51-67, 1997.

T. León, V. Liern, J. L. Ruízy I. Sirvent. A Posibilistic Programming Approach to the Assessment of Efficiency with DEA Models. Fuzzy Sets and Systems, 139(2):407-419, 2003.

W. Cooper, S. Lawrence y K. Tone. Data envelopment analysis: A comprehensive text with models, applications, references and DEA-solver software. Springer Science y Business Media, 2007.

T Sueyoshi. Stochastic dea for restructure strategy: an application to a japanese petroleum company. The International Journal of Management Science, 28(4):385-398, 2000

Published

2018-05-31

How to Cite

[1]
H. Izquierdo Madrid, B. López de Lameda, M. E. Torres Samuel, and E. Torres Cruz, “DMU efficiency assessment using data envelopment analysis in fuzzy environment”, Publ.Cienc.Tecnol, vol. 10, no. 1, pp. 25-35, May 2018.

Issue

Section

Research Article