Abstract
The solution of PDE-constrained optimal control problems is a computationally challenging task, and it involves the solution of structured algebraic linear systems whose blocks stem from the discretized first-order optimality conditions. In this paper we analyze the numerical solution of this large-scale system: we first perform a natural order reduction, and then we solve the reduced system iteratively by exploiting specifically designed preconditioning techniques. The analysis is accompanied by numerical experiments on two application problems.
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Notes
In optimal control problems, the full rank assumption is actually an exceptional case, since it corresponds to having as many control variables as states, which is seldom encountered in practice.
The computational cost will still grow with the problem size, as basic operations are performed with longer vectors when finer discretizations are used.
With a little abuse of notation, the same letters will be used here to denote scalar functions and vectors.
We thank one of the referees for pointing this out.
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Acknowledgements
We would like to thank the anonymous referees for helpful suggestions. We are grateful to Sue Thorne for providing us with the data on the distributed control problem of Sect. 3.1. We are indebted with Michele Benzi, Eldad Haber and Lauren Taralli for making their full code available, which allowed us to extract both the data and important information for the experiments of Sect. 4.1. We also thank Michele Benzi for helpful comments on an earlier version of this manuscript.
All reported timings were obtained with Matlab [22], using the computer facilities of the SINCEM Laboratory at CIRSA, Ravenna.
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Simoncini, V. Reduced order solution of structured linear systems arising in certain PDE-constrained optimization problems. Comput Optim Appl 53, 591–617 (2012). https://doi.org/10.1007/s10589-012-9464-0
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DOI: https://doi.org/10.1007/s10589-012-9464-0