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EMOSOR: Evolutionary multiple objective optimization guided by interactive stochastic ordinal regression.

, и . Comput. Oper. Res., (2019)

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Milosz Matuschek

 

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Using a Segmenting Description approach in Multiple Criteria Decision Aiding., , и . CoRR, (2019)Data-driven preference learning methods for value-driven multiple criteria sorting with interacting criteria., , , и . CoRR, (2019)EMOSOR: Evolutionary multiple objective optimization guided by interactive stochastic ordinal regression., и . Comput. Oper. Res., (2019)Preference disaggregation method for value-based multi-decision sorting problems with a real-world application in nanotechnology., , , , , и . Knowl. Based Syst., (2021)Scoring procedures for multiple criteria decision aiding with robust and stochastic ordinal regression., и . Comput. Oper. Res., (2016)Deep dive into RNA: a systematic literature review on RNA structure prediction using machine learning methods., , , , и . Artif. Intell. Rev., 57 (9): 254 (сентября 2024)Robust indicator-based algorithm for interactive evolutionary multiple objective optimization., и . GECCO, стр. 629-637. ACM, (2019)Using Ordinal Regression for Interactive Evolutionary Multiple Objective Optimization with Multiple Decision Makers., и . GDN, том 218 из Lecture Notes in Business Information Processing, стр. 185-198. Springer, (2015)Dominance-Based Rough Set Approach to Multiple Criteria Ranking with Sorting-Specific Preference Information., , и . Challenges in Computational Statistics and Data Mining, том 605 из Studies in Computational Intelligence, Springer, (2016)Evolutionary algorithms for solving single- and multiple-objective political redistricting problems: The case study of Poland., и . Appl. Soft Comput., (2024)