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Linear transformations to decrease computational requirements of solving some known linear programming models

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  • M. Soleimani-damaneh
  • M. Zarepisheh

Abstract

Imposing additional weight restrictions increases the degeneracy and computational complexity of solving Data Envelopment Analysis (DEA) models, a known class of linear programming models. In this paper some linear transformations to reduce these problems are provided. Copyright Springer Science+Business Media, LLC 2009

Suggested Citation

  • M. Soleimani-damaneh & M. Zarepisheh, 2009. "Linear transformations to decrease computational requirements of solving some known linear programming models," Annals of Operations Research, Springer, vol. 172(1), pages 37-43, November.
  • Handle: RePEc:spr:annopr:v:172:y:2009:i:1:p:37-43:10.1007/s10479-008-0473-4
    DOI: 10.1007/s10479-008-0473-4
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    References listed on IDEAS

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    1. Boaz Golany, 1988. "Note---A Note on Including Ordinal Relations Among Multipliers in Data Envelopment Analysis," Management Science, INFORMS, vol. 34(8), pages 1029-1033, August.
    2. R. D. Banker & A. Charnes & W. W. Cooper, 1984. "Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis," Management Science, INFORMS, vol. 30(9), pages 1078-1092, September.
    3. Dyson, R. G. & Allen, R. & Camanho, A. S. & Podinovski, V. V. & Sarrico, C. S. & Shale, E. A., 2001. "Pitfalls and protocols in DEA," European Journal of Operational Research, Elsevier, vol. 132(2), pages 245-259, July.
    4. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    5. E. Thanassoulis & R. Allen, 1998. "Simulating Weights Restrictions in Data Envelopment Analysis by Means of Unobserved DMUs," Management Science, INFORMS, vol. 44(4), pages 586-594, April.
    6. R. Allen & A. Athanassopoulos & R.G. Dyson & E. Thanassoulis, 1997. "Weights restrictions and value judgements in Data Envelopment Analysis: Evolution, development and future directions," Annals of Operations Research, Springer, vol. 73(0), pages 13-34, October.
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