| Title: | A methodology for multi-label algorithm selection in constrained multiobjective optimization |
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| Authors: | ID Andova, Andrejaana, Institut "Jožef Stefan" (Author)
ID Cork, Jordan, Institut "Jožef Stefan" (Author)
ID Tušar, Tea, Institut "Jožef Stefan" (Author)
ID Filipič, Bogdan, Institut "Jožef Stefan" (Author) |
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| Files: |  URL - Source URL, visit https://www.sciencedirect.com/science/article/pii/S2210650225004031?via%3Dihub
 PDF - Presentation file, download (2,78 MB)
MD5: 699BB5CDDB653FC62BAA19E6B744D2EC
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| Language: | English |
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| Typology: | 1.01 - Original Scientific Article |
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| Organization: |  IJS - Jožef Stefan Institute
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| Abstract: | 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. |
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| Keywords: | spatial signal encoding, exploratory landscape analysis, constrained multiobjective optimization |
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| Publication status: | Published |
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| Publication version: | Version of Record |
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| Submitted for review: | 11.07.2025 |
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| Article acceptance date: | 02.12.2025 |
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| Publication date: | 07.12.2025 |
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| Publisher: | Elsevier |
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| Year of publishing: | 2025 |
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| Number of pages: | str. 1-12 |
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| Numbering: | Vol. 100, [article no.] 102246 |
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| PID: | 20.500.12556/DiRROS-28532  |
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| UDC: | 004 |
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| ISSN on article: | 2210-6510 |
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| DOI: | 10.1016/j.swevo.2025.102246 |
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| COBISS.SI-ID: | 272614147 |
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| Copyright: | © 2025 The Authors. |
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| Note: | Nasl. z nasl. zaslona;
Opis vira z dne 23. 3. 2026;
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| Publication date in DiRROS: | 23.03.2026 |
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| Views: | 179 |
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| Downloads: | 113 |
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