Search Results - "Kadziński, Miłosz"

Beyond the Arbitrariness of Drug-Likeness Rules: Rough Set Theory and Decision Rules in the Service of Drug Design.

Authors: Miebs, Grzegorz Mielniczuk, Adam Kadziński, Miłosz et al.

Source: Applied Sciences (2076-3417); Nov2024, Vol. 14 Issue 21, p9966, 14p

Deep dive into RNA: a systematic literature review on RNA structure prediction using machine learning methods.

Authors: Budnik, Michał Wawrzyniak, Jakub Grala, Łukasz et al.

Source: Artificial Intelligence Review; Sep2024, Vol. 57 Issue 9, p1-41, 41p

A Probabilistic preference learning approach for multiple criteria ranking in dynamic decision context.

Authors: Zhao, Siyuan Liu, Jiapeng Kadziński, Miłosz et al.

Source: European Journal of Operational Research; Apr2026, Vol. 330 Issue 2, p558-574, 17p

Fifty years of multi-objective optimization and decision-making: From mathematical programming to evolutionary computation.

Authors: Ehrgott, Matthias Köksalan, Murat Kadziński, Miłosz et al.

Source: European Journal of Operational Research; Apr2026, Vol. 330 Issue 1, p1-25, 25p

An Interpretable Preference Learning Model Admitting Dynamic and Context-Dependent Preferences.

Authors: Ru, Zice Liu, Jiapeng Kadziński, Miłosz et al.

Source: INFORMS Journal on Computing. Jun2026, p1. 18p.

Modeling Contingent Decision Behavior: A Bayesian Nonparametric Preference-Learning Approach.

Authors: Liu, Jiapeng Kadziński, Miłosz Liao, Xiuwu

Source: INFORMS Journal on Computing; Jul/Aug2023, Vol. 35 Issue 4, p764-785, 22p

Robust Additive Value-Based Efficiency Analysis with a Hierarchical Structure of Inputs and Outputs.

Authors: Labijak-Kowalska, Anna Kadziński, Miłosz Mrozek, Weronika

Source: Applied Sciences (2076-3417); Jun2023, Vol. 13 Issue 11, p6406, 33p

Ordinal regression meets online learning: Interactive preference learning for multiple criteria choice and ranking with provable guarantees.

Authors: Grillo, Marco Kotłowski, Wojciech Kadziński, Miłosz

Source: European Journal of Operational Research; Dec2025, Vol. 327 Issue 3, p1003-1022, 20p

Embedding carbon impact assessment in multi-criteria supplier segmentation using ELECTRE TRI-rC.

Authors: Rezaei, Jafar Kadziński, Miłosz Vana, Chrysoula et al.

Source: Annals of Operations Research; May2022, Vol. 312 Issue 2, p1445-1467, 23p

Enriched preference modeling and robustness analysis for the ELECTRE Tri-B method.

Authors: Kadziński, Miłosz Martyn, Magdalena

Source: Annals of Operations Research; Nov2021, Vol. 306 Issue 1/2, p173-207, 35p

Data-Driven Preference Learning Methods for Value-Driven Multiple Criteria Sorting with Interacting Criteria.

Authors: Liu, Jiapeng Kadziński, Miłosz Liao, Xiuwu et al.

Source: INFORMS Journal on Computing; Spring2021, Vol. 33 Issue 2, p586-606, 21p

Data-driven preference learning methods for sorting problems with multiple temporal criteria.

Authors: Li, Yijun Guo, Mengzhuo Kadziński, Miłosz et al.

Source: European Journal of Operational Research; Jun2025, Vol. 323 Issue 3, p918-937, 20p

Special Issue on "Decision Support: Combining Technology and Algorithms to Solve Complex Problems".

Authors: Kadziński, Miłosz Vetschera, Rudolf Zaraté, Pascale

Source: International Transactions in Operational Research. May2022, Vol. 29 Issue 3, p2032-2033. 2p.

Special Issue on "Decision Support: Combining Technology and Algorithms to Solve Complex Problems".

Authors: Kadziński, Miłosz Vetschera, Rudolf Zaraté, Pascale

Source: International Transactions in Operational Research. Nov2021, Vol. 28 Issue 6, p3597-3598. 2p.

Preface to the Special Issue on Decision Support: Combining Technology and Algorithms to Solve Complex Problems.

Authors: Kadziński, Miłosz Vetschera, Rudolf Zaraté, Pascale

Source: International Transactions in Operational Research. Nov2023, Vol. 30 Issue 6, p3398-3399. 2p.

A Modular Simos-Roy-Figueira framework for tailored weight elicitation in multi-criteria decision aiding.

Authors: Huang, River Kadziński, Miłosz Figueira, José Rui et al.

Source: Expert Systems with Applications; May2026, Vol. 311, pN.PAG-N.PAG, 1p

Performance evaluation of emergency department physicians using robust value‐based additive efficiency model.

Authors: Labijak‐Kowalska, Anna Kadziński, Miłosz Spychała, Inga et al.

Source: International Transactions in Operational Research. Jan2023, Vol. 30 Issue 1, p503-544. 42p. 2 Diagrams, 19 Charts, 1 Graph.

Learning user preferences in livestreaming market: A graphical model considering temporal effect.

Authors: Lin, Qingyuan Li, Yijun Kadziński, Miłosz et al.

Source: Decision Support Systems; Mar2026, Vol. 202, pN.PAG-N.PAG, 1p

Probabilistic ordinal regression methods for multiple criteria sorting admitting certain and uncertain preferences.

Authors: Ru, Zice Liu, Jiapeng Kadziński, Miłosz et al.

Source: European Journal of Operational Research; Dec2023, Vol. 311 Issue 2, p596-616, 21p

Deep preference learning for multiple criteria decision analysis.

Authors: Martyn, Krzysztof Kadziński, Miłosz

Source: European Journal of Operational Research; Mar2023, Vol. 305 Issue 2, p781-805, 25p