New Approaches in Simulation-driven Optimization

Research output: Contribution to journalConference articlepeer-review


This paper presents a work regarding the integration of discriminant functions (classifiers) with search algorithms to tackle the problem of failed simulation runs. The discriminant output is used to guide the search towards better solutions while minimizing adverse effects. The search is managed with a trust-region approach for convergence in the presence of prediction inaccuracies. Numerical evaluations based on engineering problem show that the approach yielded better final results in the mean and median statistics when compared to reference algorithms.

Original languageEnglish
Article number012010
JournalJournal of Physics: Conference Series
Issue number1
StatePublished - 9 Nov 2020
Event2020 3rd International Conference on Applied Mathematics, Modeling and Simulation, AMMS 2020 - Shanghai, China
Duration: 20 Sep 202021 Sep 2020


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