Adaptive Localized Reduced Basis Methods for Large Scale PDE-Constrained Optimization

Author:

Keil Tim,Ohlberger Mario,Schindler Felix

Publisher

Springer Nature Switzerland

Reference12 articles.

1. Banholzer, S., Keil, T., Ohlberger, M., Mechelli, L., Schindler, F., Volkwein, S.: An adaptive projected Newton non-conforming dual approach for trust-region reduced basis approximation of PDE-constrained parameter optimization. Pure Appl. Funct. Anal. 7(5), 1561–1596 (2022)

2. Bastian, P., et al.: The DUNE framework: basic concepts and recent developments. Comput. Math. Appl. 81, 75–112 (2021)

3. Buhr, A., Iapichino, L., Ohlberger, M., Rave, S., Schindler, F., Smetana, K.: Localized model reduction for parameterized problems. In: Model Order Reduction. Snapshot-Based Methods and Algorithms, vol. 2, pp. 245–305. Berlin: De Gruyter (2021)

4. Keil, T.: Software for: a relaxed localized trust-region reduced basis approach for optimization of multiscale problems (2023). https://doi.org/10.5281/zenodo.7821980 (2023)

5. Keil, T., Mechelli, L., Ohlberger, M., Schindler, F., Volkwein, S.: A non-conforming dual approach for adaptive trust-region reduced basis approximation of PDE-constrained parameter optimization. ESAIM Math. Model. Numer. Anal. 55(3), 1239–1269 (2021)

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