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An evolutionary approach to construction of outranking models for multicriteria classification: The case of the ELECTRE TRI method

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  • Doumpos, M.
  • Marinakis, Y.
  • Marinaki, M.
  • Zopounidis, C.

Abstract

Outranking methods constitute an important class of multicriteria classification models. Often, however, their implementation is cumbersome, due to the large number of parameters that the decision maker must specify. Past studies tried to address this issue using linear and nonlinear programming, to elicit the necessary preferential information from assignment examples. In this study, an evolutionary approach, based on the differential evolution algorithm, is proposed in the context of the ELECTRE TRI method. Computational results are given to test the effectiveness of the methodology and the quality of the obtained models.

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  • Doumpos, M. & Marinakis, Y. & Marinaki, M. & Zopounidis, C., 2009. "An evolutionary approach to construction of outranking models for multicriteria classification: The case of the ELECTRE TRI method," European Journal of Operational Research, Elsevier, vol. 199(2), pages 496-505, December.
    • Handle: RePEc:eee:ejores:v:199:y:2009:i:2:p:496-505
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    References listed on IDEAS

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    10. Paterlini, Sandra & Krink, Thiemo, 2006. "Differential evolution and particle swarm optimisation in partitional clustering," Computational Statistics & Data Analysis, Elsevier, vol. 50(5), pages 1220-1247, March.
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    Cited by:

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    2. Denis Bouyssou & Thierry Marchant & Marc Pirlot, 2023. "A theoretical look at Electre Tri-nB and related sorting models," 4OR, Springer, vol. 21(1), pages 1-31, March.
    3. Constantin Zopounidis & Michael Doumpos, 2013. "Multicriteria decision systems for financial problems," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 21(2), pages 241-261, July.
    4. Eduardo Fernandez & Jorge Navarro & Edgar Covantes & Jorge Rodriguez, 2017. "Analysis of the effectiveness of the theseus multi-criteria sorting method: theoretical remarks and experimental evidence," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 25(2), pages 314-339, July.
    5. Eduardo Fernández & José Rui Figueira & Jorge Navarro, 2023. "A theoretical look at ordinal classification methods based on comparing actions with limiting boundaries between adjacent classes," Annals of Operations Research, Springer, vol. 325(2), pages 819-843, June.
    6. Andriosopoulos, Dimitrios & Gaganis, Chrysovalantis & Pasiouras, Fotios & Zopounidis, Constantin, 2012. "An application of multicriteria decision aid models in the prediction of open market share repurchases," Omega, Elsevier, vol. 40(6), pages 882-890.
    7. Pegdwendé Minoungou & Vincent Mousseau & Wassila Ouerdane & Paolo Scotton, 2023. "A MIP-based approach to learn MR-Sort models with single-peaked preferences," Annals of Operations Research, Springer, vol. 325(2), pages 795-817, June.
    8. Tsionas, Mike G., 2019. "Multi-objective optimization using statistical models," European Journal of Operational Research, Elsevier, vol. 276(1), pages 364-378.
    9. Govindan, Kannan & Jepsen, Martin Brandt, 2016. "ELECTRE: A comprehensive literature review on methodologies and applications," European Journal of Operational Research, Elsevier, vol. 250(1), pages 1-29.
    10. 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.
    11. Martyn, Krzysztof & Kadziński, Miłosz, 2023. "Deep preference learning for multiple criteria decision analysis," European Journal of Operational Research, Elsevier, vol. 305(2), pages 781-805.
    12. Fernández, Eduardo & Figueira, José Rui & Navarro, Jorge, 2019. "An interval extension of the outranking approach and its application to multiple-criteria ordinal classification," Omega, Elsevier, vol. 84(C), pages 189-198.
    13. Fernández, Eduardo & Figueira, José Rui & Navarro, Jorge, 2020. "Interval-based extensions of two outranking methods for multi-criteria ordinal classification," Omega, Elsevier, vol. 95(C).
    14. Rolland, Antoine, 2013. "Reference-based preferences aggregation procedures in multi-criteria decision making," European Journal of Operational Research, Elsevier, vol. 225(3), pages 479-486.
    15. Eduardo Fernandez & Jorge Navarro & Rafael Olmedo, 2018. "Characterization of the Effectiveness of Several Outranking-Based Multi-Criteria Sorting Methods," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 17(04), pages 1047-1084, July.
    16. Fernández, Eduardo & Figueira, José Rui & Navarro, Jorge & Solares, Efrain, 2022. "Handling imperfect information in multiple criteria decision-making through a comprehensive interval outranking approach," Socio-Economic Planning Sciences, Elsevier, vol. 82(PB).
    17. Doumpos, Michael & Zopounidis, Constantin, 2011. "Preference disaggregation and statistical learning for multicriteria decision support: A review," European Journal of Operational Research, Elsevier, vol. 209(3), pages 203-214, March.
    18. Khaled Belahcène & Vincent Mousseau & Wassila Ouerdane & Marc Pirlot & Olivier Sobrie, 2023. "Multiple criteria sorting models and methods—Part I: survey of the literature," 4OR, Springer, vol. 21(1), pages 1-46, March.
    19. Fernandez, Eduardo & Navarro, Jorge, 2011. "A new approach to multi-criteria sorting based on fuzzy outranking relations: The THESEUS method," European Journal of Operational Research, Elsevier, vol. 213(2), pages 405-413, September.
    20. Doumpos, Michalis & Figueira, José Rui, 2019. "A multicriteria outranking approach for modeling corporate credit ratings: An application of the Electre Tri-nC method," Omega, Elsevier, vol. 82(C), pages 166-180.

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