20.500.12556/DiRROS-28532 A methodology for multi-label algorithm selection in constrained multiobjective optimization Algorithm selection in optimization is often done by considering a single best-performing algorithm per problem. However, sometimes multiple algorithms perform comparably well on the same optimization problem, and in such cases, it would be appropriate to consider all of them as best performing. Hence, this work proposes an algorithm selection methodology that enables the identification and prediction of multiple algorithms as best performing. More specifically, the methodology involves first identifying the best-performing algorithms using statistical tests that show when the algorithms perform comparably well. Then, these algorithms are set as targets to machine learning models that can predict multiple algorithms as best performing. Finally, an evaluation measure is introduced to assess the performance of the algorithm selection models. The proposed methodology is applied to constrained multiobjective optimization. spatial signal encoding exploratory landscape analysis constrained multiobjective optimization izbira algoritmov optimizacija true false true Elsevier Angleški jezik Slovenski jezik © 2025 The Authors. Neznano 2026-03-23 13:17:26 2026-03-23 13:17:26 2026-03-26 04:05:45 0000-00-00 00:00:00 2025 0 0 Nasl. z nasl. zaslona; Opis vira z dne 23. 3. 2026; str. 1-12 Vol. 100, [article no.] 102246 Jan. 2026 0000-00-00 Zaloznikova Objavljeno NiDoloceno 2025-07-11 2025-12-02 2025-12-07 004 2210-6510 10.1016/j.swevo.2025.102246 272614147 https://www.sciencedirect.com/science/article/pii/S2210650225004031?via%3Dihub 1 431a22b6-26b2-11f1-aa40-001a4af901a5 https://dirros.openscience.si/Dokument.php?lang=slv&id=42319 RAZ_Andova_Andrejaana_2025.pdf RAZ_Andova_Andrejaana_2025.pdf 1 699BB5CDDB653FC62BAA19E6B744D2EC c9d829fbb52f004a4b43acf9927d761a413f038890573c109298096b91b4853c 967088c1-26b2-11f1-aa40-001a4af901a5 https://dirros.openscience.si/Dokument.php?lang=slv&id=42323 Institut Jožef Stefan 0 0 0