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Ranking Alternatives based on Imprecise Multi-Criteria Data and Pairwise Overlap Dominance Relations

Author

Listed:
  • Camilo Franco

    () (Department of Food and Resource Economics, University of CopenhagenAuthor-Name: Jens Leth Hougaard)

  • Jens Leth Hougaard

    () (Department of Food and Resource Economics, University of Copenhagen)

  • Kurt Nielsen

    () (Department of Food and Resource Economics, University of Copenhagen)

Abstract

This paper explores a multi-criteria outranking methodology that is designed to both handle uncertain and imprecise data in describing alternatives as well as treating the decision maker's preference information in a sensible way that re flects the difficulties in articulating preferences. Based on fuzzy interval degrees, representing and measuring data imprecision, this procedure obtains a set of semi-equivalence classes assigning an intransitive order on the alternatives. Relevance measures are then explored for ranking alternatives with respect to the semi-equivalence classes, and a final illustrative example is given for comparison with standard methods like PROMETHEE. The proposed methodology takes into account the risk attitudes of decision makers, organizing the alternatives and ranking them according to their relevance. The whole interactive decision support allows understanding the dependencies among the alternatives and how they can be resolved if a finer ranking is preferred.

Suggested Citation

  • Camilo Franco & Jens Leth Hougaard & Kurt Nielsen, 2014. "Ranking Alternatives based on Imprecise Multi-Criteria Data and Pairwise Overlap Dominance Relations," MSAP Working Paper Series 02_2014, University of Copenhagen, Department of Food and Resource Economics.
  • Handle: RePEc:foi:msapwp:02_2014
    as

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    File URL: http://okonomi.foi.dk/workingpapers/MSAPpdf/MSAP2014/MSAP_WP02_2014.pdf
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    References listed on IDEAS

    as
    1. Dubois, Didier, 2006. "Possibility theory and statistical reasoning," Computational Statistics & Data Analysis, Elsevier, vol. 51(1), pages 47-69, November.
    2. Jens Leth Hougaard & Kurt Nielsen, 2011. "Weighted Overlap Dominance - A Procedure for Interactive Selection on Multidimensional Interval Data," MSAP Working Paper Series 06_2010, University of Copenhagen, Department of Food and Resource Economics.
    3. Hatami-Marbini, Adel & Tavana, Madjid, 2011. "An extension of the Electre I method for group decision-making under a fuzzy environment," Omega, Elsevier, vol. 39(4), pages 373-386, August.
    4. Cohen, Michele & Jaffray, Jean-Yves, 1980. "Rational Behavior under Complete Ignorance," Econometrica, Econometric Society, vol. 48(5), pages 1281-1299, July.
    5. Le Teno, J. F. & Mareschal, B., 1998. "An interval version of PROMETHEE for the comparison of building products' design with ill-defined data on environmental quality," European Journal of Operational Research, Elsevier, vol. 109(2), pages 522-529, September.
    6. Hougaard, Jens Leth, 1999. "Fuzzy scores of technical efficiency," European Journal of Operational Research, Elsevier, vol. 115(3), pages 529-541, June.
    7. Goumas, M. & Lygerou, V., 2000. "An extension of the PROMETHEE method for decision making in fuzzy environment: Ranking of alternative energy exploitation projects," European Journal of Operational Research, Elsevier, vol. 123(3), pages 606-613, June.
    8. Opricovic, Serafim & Tzeng, Gwo-Hshiung, 2007. "Extended VIKOR method in comparison with outranking methods," European Journal of Operational Research, Elsevier, vol. 178(2), pages 514-529, April.
    9. Behzadian, Majid & Kazemzadeh, R.B. & Albadvi, A. & Aghdasi, M., 2010. "PROMETHEE: A comprehensive literature review on methodologies and applications," European Journal of Operational Research, Elsevier, vol. 200(1), pages 198-215, January.
    10. Wade D. Cook & Moshe Kress, 1990. "A Data Envelopment Model for Aggregating Preference Rankings," Management Science, INFORMS, vol. 36(11), pages 1302-1310, November.
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    More about this item

    Keywords

    Weighted overlap dominance; fuzzy interval data; imprecision measures; semi-equivalence classes; relevance ranking;

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