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A linear programming approach for learning non-monotonic additive value functions in multiple criteria decision aiding

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Cited by:

  1. Gilbert, Hugo & Ouaguenouni, Mohamed & Öztürk, Meltem & Spanjaard, Olivier, 2025. "Robust ordinal regression for subsets comparisons with interactions," European Journal of Operational Research, Elsevier, vol. 320(1), pages 146-159.
  2. 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.
  3. Arribas, I. & Urbano, A., 2018. "Identification of efficient equilibria in multiproduct trading with indivisibilities and non-monotonicity," Journal of Mathematical Economics, Elsevier, vol. 79(C), pages 83-94.
  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. Kadziński, Miłosz & Ghaderi, Mohammad & Dąbrowski, Maciej, 2020. "Contingent preference disaggregation model for multiple criteria sorting problem," European Journal of Operational Research, Elsevier, vol. 281(2), pages 369-387.
  7. Liu, Jiapeng & Liao, Xiuwu & Kadziński, Miłosz & Słowiński, Roman, 2019. "Preference disaggregation within the regularization framework for sorting problems with multiple potentially non-monotonic criteria," European Journal of Operational Research, Elsevier, vol. 276(3), pages 1071-1089.
  8. Podinovski, Vladislav V., 2020. "Maximum likelihood solutions for multicriterial choice problems," European Journal of Operational Research, Elsevier, vol. 286(1), pages 299-308.
  9. Guo, Mengzhuo & Zhang, Qingpeng & Liao, Xiuwu & Chen, Frank Youhua & Zeng, Daniel Dajun, 2021. "A hybrid machine learning framework for analyzing human decision-making through learning preferences," Omega, Elsevier, vol. 101(C).
  10. Xingli Wu & Huchang Liao, 2021. "Learning judgment benchmarks of customers from online reviews," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 43(4), pages 1125-1157, December.
  11. Guo, Mengzhuo & Liao, Xiuwu & Liu, Jiapeng & Zhang, Qingpeng, 2020. "Consumer preference analysis: A data-driven multiple criteria approach integrating online information," Omega, Elsevier, vol. 96(C).
  12. 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.
  13. 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.
  14. Ghaderi, Mohammad & Kadziński, Miłosz, 2021. "Incorporating uncovered structural patterns in value functions construction," Omega, Elsevier, vol. 99(C).
  15. Dias, Luis C. & Dias, Joana & Ventura, Tiago & Rocha, Humberto & Ferreira, Brígida & Khouri, Leila & Lopes, Maria do Carmo, 2022. "Learning target-based preferences through additive models: An application in radiotherapy treatment planning," European Journal of Operational Research, Elsevier, vol. 302(1), pages 270-279.
  16. Kadziński, Miłosz & Wójcik, Michał & Ciomek, Krzysztof, 2022. "Review and experimental comparison of ranking and choice procedures for constructing a univocal recommendation in a preference disaggregation setting," Omega, Elsevier, vol. 113(C).
  17. Arwa Khannoussi & Antoine Rolland & Julien Velcin, 2025. "A multidimensional spatial model for preference representation in multi-criteria group decision aiding," 4OR, Springer, vol. 23(2), pages 163-191, June.
  18. 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.
  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. Luis C. Dias & Gabriela D. Oliveira & Paula Sarabando, 2021. "Choice-based preference disaggregation concerning vehicle technologies," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 29(1), pages 177-200, March.
  21. 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).
  22. Gehrlein, Jonas & Miebs, Grzegorz & Brunelli, Matteo & Kadziński, Miłosz, 2023. "An active preference learning approach to aid the selection of validators in blockchain environments," Omega, Elsevier, vol. 118(C).
  23. Zhou, Kun & Gong, Zaiwu & Wei, Guo & Słowiński, Roman, 2025. "Preference disaggregation analysis with criteria selection in a regularization framework," Omega, Elsevier, vol. 133(C).
  24. Susmaga, Robert & Szczȩch, Izabela & Zielniewicz, Piotr & Brzezinski, Dariusz, 2023. "MSD-space: Visualizing the inner-workings of TOPSIS aggregations," European Journal of Operational Research, Elsevier, vol. 308(1), pages 229-242.
  25. Yue Qi & Ralph E. Steuer, 2020. "On the analytical derivation of efficient sets in quad-and-higher criterion portfolio selection," Annals of Operations Research, Springer, vol. 293(2), pages 521-538, October.
  26. Subrata Mitra & Balram Avittathur, 2018. "Application of linear programming in optimizing the procurement and movement of coal for an Indian coal-fired power-generating company," DECISION: Official Journal of the Indian Institute of Management Calcutta, Springer;Indian Institute of Management Calcutta, vol. 45(3), pages 207-224, September.
  27. Mohammad Ghaderi & Milosz Kadzinsky, 2019. "Accounting for structural patterns in construction of value functions: a convex optimization approach," Economics Working Papers 1634, Department of Economics and Business, Universitat Pompeu Fabra.
  28. Wachowicz, Tomasz & Roszkowska, Ewa, 2022. "Can holistic declaration of preferences improve a negotiation offer scoring system?," European Journal of Operational Research, Elsevier, vol. 299(3), pages 1018-1032.
  29. Sarah Ben Amor & Fateh Belaid & Ramzi Benkraiem & Boumediene Ramdani & Khaled Guesmi, 2023. "Multi-criteria classification, sorting, and clustering: a bibliometric review and research agenda," Annals of Operations Research, Springer, vol. 325(2), pages 771-793, June.
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