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Organisation profile

Organisation profile

Die Forschungsgruppe modelliert und optimiert Aufgaben vornehmlich aus den Bereichen Produktion und Logistik. Zur Anwendung kommen dabei simulationsbasierte Ansätze in Kombination mit heuristischen Optimierungsverfahren und verschiedenen Data-Mining Ansätzen. Im Bereich der intelligenten Datenanalyse liegt ein besonderer Forschungsschwerpunkt auf der interpretationsfähigen Datenanalyse (Whitebox Data Mining).  

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Collaborations and top research areas from the last five years

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  • A Comparative Study of Model Selection Criteria for Symbolic Regression

    Soltani, A., Kronberger, G., Olivetti De Franca, F., Billa, M. & Lucantonio, A., 10 Jul 2026, GECCO 2026 - Proceedings of the 2026 Genetic and Evolutionary Computation Conference. Association for Computing Machinery, Inc, p. 826-833 8 p. (GECCO 2026 - Proceedings of the 2026 Genetic and Evolutionary Computation Conference).

    Research output: Chapter in Book/Report/Conference proceedings › Conference contribution › peer-review

    Open Access
  • A Privacy-Preserving Approach for Collaborative Optimization Across Company Borders

    Nguyen Duy, D., Fischer, B., Solina, V. & Affenzeller, M., 1 Jan 2026, In: IET Collaborative Intelligent Manufacturing. 8, 1, e70063.

    Research output: Contribution to journal › Article › peer-review

    Open Access
  • Comparative Analysis of Model Selection Criteria for Symbolic Regression Using Genetic Programming

    Ramlan, F. W., Kronberger, G., O’Riordan, C. & McDermott, J., 2026, Computational Intelligence - 17th International Joint Conference, IJCCI 2025, Proceedings. Marcelloni, F., Madani, K., van Stein, N. & Filipe, J. (eds.). Springer, p. 91-108 18 p. (Communications in Computer and Information Science; vol. 2828 CCIS).

    Research output: Chapter in Book/Report/Conference proceedings › Conference contribution › peer-review

    2 Citations (Scopus)