IDEAS home Printed from https://ideas.repec.org/r/eee/ejores/v281y2020i2p369-387.html

Contingent preference disaggregation model for multiple criteria sorting problem

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as


Cited by:

  1. Ru, Zice & Liu, Jiapeng & Kadziński, Miłosz & Liao, Xiuwu, 2022. "Bayesian ordinal regression for multiple criteria choice and ranking," European Journal of Operational Research, Elsevier, vol. 299(2), pages 600-620.
  2. Khaled Belahcène & Vincent Mousseau & Wassila Ouerdane & Marc Pirlot & Olivier Sobrie, 2023. "Multiple criteria sorting models and methods. Part II: theoretical results and general issues," 4OR, Springer, vol. 21(2), pages 181-204, June.
  3. Li, Zhuolin & Zhang, Zhen & Pedrycz, Witold, 2025. "An incremental preference elicitation-based approach to learning potentially non-monotonic preferences in multi-criteria sorting," European Journal of Operational Research, Elsevier, vol. 323(2), pages 553-570.
  4. Li, Zhuolin & Zhang, Zhen & Pedrycz, Witold, 2025. "Integrating machine learning models to learn potentially non-monotonic preferences for multi-criteria sorting from large-scale assignment examples," Omega, Elsevier, vol. 131(C).
  5. Bagherzadeh, Mehdi & Ghaderi, Mohammad & Fernandez, Anne-Sophie, 2022. "Coopetition for innovation - the more, the better? An empirical study based on preference disaggregation analysis," European Journal of Operational Research, Elsevier, vol. 297(2), pages 695-708.
  6. Marco Cinelli & Matteo Spada & Wansub Kim & Yiwen Zhang & Peter Burgherr, 2021. "MCDA Index Tool: an interactive software to develop indices and rankings," Environment Systems and Decisions, Springer, vol. 41(1), pages 82-109, March.
  7. Wu, Xingli & Zhu, Ting, 2025. "From data to diagnosis: A logical learning method to enhance interpretability in bipolar and major depressive disorder identification," European Journal of Operational Research, Elsevier, vol. 325(2), pages 362-380.
  8. Wen, Zhi & Liao, Huchang & Figueira, José Rui, 2024. "A preference disaggregation-driven multiple criteria sorting model based on regret theory," Omega, Elsevier, vol. 129(C).
  9. Leyva López, Juan Carlos & Solano Noriega, Jesús Jaime & Figueira, José Rui & Liu, Jun & Gastélum Chavira, Diego Alonso, 2021. "Non-dominated sorting genetic-based algorithm for exploiting a large-sized fuzzy outranking relation," European Journal of Operational Research, Elsevier, vol. 293(2), pages 615-631.
  10. Khaled Belahcène & Vincent Mousseau & Wassila Ouerdane & Marc Pirlot & Olivier Sobrie, 2024. "A guided tour of multiple criteria sorting models and methods," Annals of Operations Research, Springer, vol. 343(2), pages 785-845, December.
  11. Podinovski, Vladislav V., 2020. "Maximum likelihood solutions for multicriterial choice problems," European Journal of Operational Research, Elsevier, vol. 286(1), pages 299-308.
  12. Marco Corazza & Giovanni Fasano & Stefania Funari & Riccardo Gusso, 2021. "MURAME parameter setting for creditworthiness evaluation: data-driven optimization," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 44(1), pages 295-339, June.
  13. Liu, Jiapeng & Kadziński, Miłosz & Liao, Xiuwu & Mao, Xiaoxin & Wang, Yao, 2020. "A preference learning framework for multiple criteria sorting with diverse additive value models and valued assignment examples," European Journal of Operational Research, Elsevier, vol. 286(3), pages 963-985.
  14. Kadziński, Miłosz & Ciomek, Krzysztof, 2021. "Active learning strategies for interactive elicitation of assignment examples for threshold-based multiple criteria sorting," European Journal of Operational Research, Elsevier, vol. 293(2), pages 658-680.
  15. Ghaderi, Mohammad, 2022. "Public health interventions in the face of pandemics: Network structure, social distancing, and heterogeneity," European Journal of Operational Research, Elsevier, vol. 298(3), pages 1016-1031.
  16. Ghaderi, Mohammad & Kadziński, Miłosz, 2021. "Incorporating uncovered structural patterns in value functions construction," Omega, Elsevier, vol. 99(C).
  17. Tlili, Ali & Belahcène, Khaled & Khaled, Oumaima & Mousseau, Vincent & Ouerdane, Wassila, 2022. "Learning non-compensatory sorting models using efficient SAT/MaxSAT formulations," European Journal of Operational Research, Elsevier, vol. 298(3), pages 979-1006.
  18. Bas Donkers & Mohammad Ghaderi & Kamel Jedidi & Miłosz Kadziński, 2025. "Random Preference Model," Working Papers 1502, Barcelona School of Economics.
  19. Li, Yijun & Guo, Mengzhuo & Kadziński, Miłosz & Zhang, Qingpeng & Xu, Chenxi, 2025. "Data-driven preference learning methods for sorting problems with multiple temporal criteria," European Journal of Operational Research, Elsevier, vol. 323(3), pages 918-937.
  20. Kadziński, Miłosz & Wójcik, Michał & Ghaderi, Mohammad, 2025. "From investigation of expressiveness and robustness to a comprehensive value-based framework for multiple criteria sorting problems," Omega, Elsevier, vol. 131(C).
  21. Amoussou, Manuel & Belahcene, Khaled & Maudet, Nicolas & Mousseau, Vincent & Ouerdane, Wassila, 2026. "Designing and computing explanations for comparisons inferred from an additive value model," European Journal of Operational Research, Elsevier, vol. 328(1), pages 232-245.
  22. Yu Yang & Yelin Fu & Siying Chen, 2026. "Group Preference Construction with Attitudinal Consensus Building Based on Uncertain Preference Disaggregation Analysis," Group Decision and Negotiation, Springer, vol. 35(2), pages 1-31, June.
  23. Jiapeng Liu & Miłosz Kadziński & Xiuwu Liao, 2023. "Modeling Contingent Decision Behavior: A Bayesian Nonparametric Preference-Learning Approach," INFORMS Journal on Computing, INFORMS, vol. 35(4), pages 764-785, July.
  24. Ru, Zice & Liu, Jiapeng & Kadziński, Miłosz & Liao, Xiuwu, 2023. "Probabilistic ordinal regression methods for multiple criteria sorting admitting certain and uncertain preferences," European Journal of Operational Research, Elsevier, vol. 311(2), pages 596-616.
  25. Cinelli, Marco & Kadziński, Miłosz & Miebs, Grzegorz & Gonzalez, Michael & Słowiński, Roman, 2022. "Recommending multiple criteria decision analysis methods with a new taxonomy-based decision support system," European Journal of Operational Research, Elsevier, vol. 302(2), pages 633-651.
  26. Mohammad Ghaderi & Kamel Jedidi & Miłosz Kadziński & Bas Donkers, 2025. "Random preference model," Economics Working Papers 1913, Department of Economics and Business, Universitat Pompeu Fabra.
  27. Mei Cai & Xue Zhang, 2025. "Consumer preference analysis integrating online reviews: a multiple criteria group approach considering individual stochastic behavior," 4OR, Springer, vol. 23(1), pages 97-122, March.
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.