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Optimal solution of technology selection model: a computational efficient form

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Abstract

This paper introduces a computational efficient form to find the optimal solution of technology selection model. The paper suggests an efficient and simple method to obtain the optimal solution of linear programming (LP) problem used in technology selection without the need for solving any LP. Clearly, the contribution of this study is that it improves further the computational complexity of the literature, which is significant when dealing with complexity.

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References

  1. Karsak EE, Ahiska SS (2005) Practical common weight multi-criteria decision-making approach with an improved discriminating power for technology selection. Int J Prod Res 43(8):1537–1554. doi:10.1080/13528160412331326478

    Article  MATH  Google Scholar 

  2. Amin GR, Toloo M, Sohrabi B (2006) An improved MCDM DEA model for technology selection. Int J Prod Res 44(13):2681–2686. doi:10.1080/00207540500472754

    Article  MATH  Google Scholar 

  3. Booth DE, Khouja M, Hu M (1992) A robust multivariate statistical procedure for evaluation and selection of industrial robots. Int J Oper Prod Manage 12:15–24. doi:10.1108/01443579210009023

    Article  Google Scholar 

  4. Khouja M (1995) The use of data envelopment analysis for technology selection. Comput Ind Eng 28:123–132. doi:10.1016/0360-8352(94)00032-I

    Article  Google Scholar 

  5. Braglia M, Petroni A (1999) Evaluating and selecting investments in industrial robots. Int J Prod Res 37:4157–4178. doi:10.1080/002075499189718

    Article  MATH  Google Scholar 

  6. Charnes A, Cooper WW, Rhodes E (1978) Measuring the efficiency of decision making units. Eur J Oper Res 2(6):429–444. doi:10.1016/0377-2217(78)90138-8

    Article  MATH  MathSciNet  Google Scholar 

  7. Cooper WW, Seiford LM, Tone K (2006) Introduction to data envelopment analysis and its uses with DEA-solver software and references. Springer, New York

    Google Scholar 

  8. Emrouznejad A, Tavares G, Parker B (2008) A bibliography of data envelopment analysis (1978–2003). Socio Eco Plan Sci doi:10.1016/j.seps.2007. 07.002

  9. Dulá JH (2008) A computational study of DEA with massive data sets. Comput Oper Res 35:1191–1203. doi:10.1016/j.cor.2006.07.011

    Article  MATH  Google Scholar 

  10. Barr RS, Durchholz ML (1997) Parallel and hierarchical decomposition approaches for solving large-scale data envelopment analysis models. Ann Oper Res 73:339–372. doi:10.1023/A:1018941531019

    Article  MATH  Google Scholar 

  11. Amin GR, Toloo M (2004) A polynomial-time algorithm for finding epsilon in DEA models. Comput Oper Res 31:803–805. doi:10.1016/S0305-0548(03)00072-8

    Article  MATH  MathSciNet  Google Scholar 

  12. Talluri S, Yoon KP (2000) A cone-ratio DEA approach for AMT justification. Int J Prod Econ 66:119–129. doi:10.1016/S0925-5273(99)00123-1

    Article  Google Scholar 

  13. Sun S (2002) Assessing computer numerical control machines using data envelopment analysis. Int J Prod Res 40:2011–2039. doi:10.1080/00207540210123634

    Article  MATH  Google Scholar 

  14. Farzipoor SR (2008) Technology selection in the presence of imprecise data, weight restrictions, and nondiscretionary factors. Int J Adv Manuf Technol doi:10.1007/s00170-008-1514-5

  15. Cook WD, Kress M, Seiford LM (1996) Data envelopment analysis in the presence of both quantitative and qualitative factors. J Oper Res Soc 47:945–953

    Article  MATH  Google Scholar 

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Authors and Affiliations

  1. Department of Computer Engineering, Postgraduate Engineering Centre, Islamic Azad University of South Tehran Branch, Tehran, Iran

    Gholam R. Amin

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  1. Gholam R. Amin
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Correspondence to Gholam R. Amin.

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Amin, G.R. Optimal solution of technology selection model: a computational efficient form. Int J Adv Manuf Technol 43, 1046–1050 (2009). https://doi.org/10.1007/s00170-008-1787-8

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  • DOI: https://doi.org/10.1007/s00170-008-1787-8

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