Analysis of Multi Attribute Decision Making Problems by Using of Data Envelopment Analysis Technique

Authors

1 Department of Industrial Engineering, Najafabad Branch, Islamic Azad University, Najafabad, Iran

2 Department of Management, Isfahan University, Isfahan, Iran

Abstract

Data Envelopment Analysis (DEA) is used for calculating of relative efficiency and then ranking of decision making units (DMU) subject to inputs and outputs in a continuous decision making   space. In this paper, DEA models, Cook and Kress Model and Belton-Vickers model have been applied as a multi attribute decision making (MADM) tool and compared analytically to other MADM models such as simple additive weighted (SAW) and technique for order preference by similarity to ideal solution (TOPSIS). For this purpose, after simulating some decision making matrixes and replacing DMU with alternatives, outputs with criteria to be maximized, inputs with criteria to be minimized, alternatives will be ranked by these models. The results of this study show that incorporating decision maker value judgments into the DEA models (restricted DEA models) provide comparable results to traditional MADM models (such as SAW and TOPSIS that are applied more than others). So, restricted DEA models seem to be an advantageous tool for solving MADM problems.

Keywords

References

Adler, N, Friedman, L and Sinuany-Stern, Z (2002) “Review of ranking methods in the data envelopment analysis context “, European Journal of Operational Research , Vol. 140, pp. 249-265.

Belton, V and Vickers, S.P (1992) “ VIDEA: integrated DEA and MCDA- A visual interactive approach “ , Proceedings of the Tenth International Conference on Multiple Criteria Decision Making , Vol. 2, pp. 419-429.

Bouyssou, D. (1999)”Using DEA as a tool for MCDM : some remarks” , Journal of the Operational Research Society,Vol. 50, pp. 974-978.

Cook, W.D and kress, M.(1994) “A multiple-criteria composite index model for quantitative and qualitative data “, European Journal of Operational Research, Vol. 78, pp. 367-379.

Cook, W.D and Seiford, L.M. (2009),”Data envelopment analysis (DEA) – Thirty years on”, European Journal of Operational Research, Vol. 192, pp. 1-17.

Cooper, W.W, Seiford, L.M and Tone, K.(2006) Introduction To Data Envelopment Analysis and Its Uses , USA , NY : Springer.

Doyle, JR and Green, R.H.(1993)”Data Envelopment Analysis and Multiple Criteria Decision Making”, OMEGA, Vol. 21, No. 6, pp. 713-715.

Ishizaka, A and Nemery, P, (2013) Multi-Criteria Decision Analysis – Methods and Software , United Kingdom, John Wiley & Sons.

Sarkis,J,(2000)”A comparative analysis of DEA as a discrete alternative multiple criteria decision tool”, European Journal of Operational Research, Vol. 123, pp. 543-557.

Stewart, t.(1996)”Relationships between Data Envelopment Analysis and Multi criteria Decision Analysis ”, Journal of the Operational Research Society,Vol. 47, pp. 654-665.

Shanling, LI , Jahanshahloo, G.R and Khodabakhshi, M.(2007)” A super-efficiency model for ranking efficient units in data envelopment analysis”, Applied Mathematics and Computation, Vol. 184, pp. 638–648.

Venkata Rao, R. (2013) Decision Making in the Manufacturing Environment Using Graph Theory and Fuzzy Multiple Attribute Decision Making Methods, USA, NY: Springer

Zhu, J.(2009) Quantitative Models for Performance Evaluation and Benchmarking , USA, NY: Springer.

Journal of Applied Research on Industrial Engineering

Volume 1, Issue 4
Autumn 2014
Pages 198-207

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History

  • Receive Date: 15 September 2014
  • Revise Date: 02 October 2014
  • Accept Date: 05 October 2014

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