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A flexible approach to ranking with an application to MBA Programs

  • Köksalan, Murat
  • Büyükbasaran, Tayyar
  • Özpeynirci, Özgür
  • Wallenius, Jyrki

We develop a model for flexibly ranking multi-dimensional alternatives/units into preference classes via Mixed Integer Programming. We consider a linear aggregation model, but allow the criterion weights to vary within pre-specified ranges. This allows the individual alternatives/units to play to their strengths. We illustrate the use of the model by considering the Financial Times Global MBA Program rankings and discuss the implications. We argue that in many applications neither the data nor the weights or the aggregation model itself is precise enough to warrant a complete ranking, providing an argument for sorting or what we call flexible ranking.

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File URL: http://www.sciencedirect.com/science/article/pii/S0377-2217(09)00143-X
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Article provided by Elsevier in its journal European Journal of Operational Research.

Volume (Year): 201 (2010)
Issue (Month): 2 (March)
Pages: 470-476

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Handle: RePEc:eee:ejores:v:201:y:2010:i:2:p:470-476
Contact details of provider: Web page: http://www.elsevier.com/locate/eor

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  1. Cook, Wade D., 2006. "Distance-based and ad hoc consensus models in ordinal preference ranking," European Journal of Operational Research, Elsevier, vol. 172(2), pages 369-385, July.
  2. Ralph E. Steuer, 1976. "Multiple Objective Linear Programming with Interval Criterion Weights," Management Science, INFORMS, vol. 23(3), pages 305-316, November.
  3. Arbel, Ami & Vargas, Luis G., 1993. "Preference simulation and preference programming: robustness issues in priority derivation," European Journal of Operational Research, Elsevier, vol. 69(2), pages 200-209, September.
  4. Ray, Subhash C. & Jeon, Yongil, 2008. "Reputation and efficiency: A non-parametric assessment of America's top-rated MBA programs," European Journal of Operational Research, Elsevier, vol. 189(1), pages 245-268, August.
  5. Wang, Ying-Ming & Elhag, Taha M.S., 2007. "A goal programming method for obtaining interval weights from an interval comparison matrix," European Journal of Operational Research, Elsevier, vol. 177(1), pages 458-471, February.
  6. Katrin Borcherding & Thomas Eppel & Detlof von Winterfeldt, 1991. "Comparison of Weighting Judgments in Multiattribute Utility Measurement," Management Science, INFORMS, vol. 37(12), pages 1603-1619, December.
  7. Zopounidis, Constantin & Doumpos, Michael, 2002. "Multicriteria classification and sorting methods: A literature review," European Journal of Operational Research, Elsevier, vol. 138(2), pages 229-246, April.
  8. Zopounidis, Constantin, 2002. "MCDA methodologies for classification and sorting," European Journal of Operational Research, Elsevier, vol. 138(2), pages 227-228, April.
  9. Adler, Nicole & Friedman, Lea & Sinuany-Stern, Zilla, 2002. "Review of ranking methods in the data envelopment analysis context," European Journal of Operational Research, Elsevier, vol. 140(2), pages 249-265, July.
  10. Mustajoki, Jyri & Hamalainen, Raimo P. & Lindstedt, Mats R.K., 2006. "Using intervals for global sensitivity and worst-case analyses in multiattribute value trees," European Journal of Operational Research, Elsevier, vol. 174(1), pages 278-292, October.
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