Low-regret shape optimization in the presence of missing Dirichlet data

Abstract A shape optimization problem subject to an elliptic equation in the presence of missing data on the Dirichlet boundary condition is considered. It is formulated by optimizing the deformation field that varies the spatial domain where the Poisson equation is posed. To take into consideration the missing boundary data the problem is formulated as a no-regret problem and approximated by low-regret problems. This approach allows to obtain deformation fields that are robust against the missing information. The formulation of the regret problems was achieved by employing the Fenchel transform. Convergence of the solutions of the low-regret to the no-regret problems is analyzed, the gradient of the cost is characterized and a first order numerical method is proposed. Numerical examples illustrate the robustness of the low-regret deformation fields with respect to missing data. To the best of our knowledge, this is the first time that a numerical investigation is reported on the level of effectiveness of the low-regret approach in the presence of missing data in an optimal control problem.

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Publication Details

Journal
Inverse Problems
Published
2025-08-18
DOI
https://doi.org/10.1088/1361-6420/adfc91
Primary Topic
Color perception and design
Type
article
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article

Low-regret shape optimization in the presence of missing Dirichlet data

John Sebastian H. Simon, Karl Kunisch
Inverse Problems
Color perception and design
article

Low-regret shape optimization in the presence of missing Dirichlet data

John Sebastian H. Simon, Karl Kunisch
article en

Abstract

Abstract A shape optimization problem subject to an elliptic equation in the presence of missing data on the Dirichlet boundary condition is considered. It is formulated by optimizing the deformation field that varies the spatial domain where the Poisson equation is posed. To take into consideration the missing boundary data the problem is formulated as a no-regret problem and approximated by low-regret problems. This approach allows to obtain deformation fields that are robust against the missing information. The formulation of the regret problems was achieved by employing the Fenchel transform. Convergence of the solutions of the low-regret to the no-regret problems is analyzed, the gradient of the cost is characterized and a first order numerical method is proposed. Numerical examples illustrate the robustness of the low-regret deformation fields with respect to missing data. To the best of our knowledge, this is the first time that a numerical investigation is reported on the level of effectiveness of the low-regret approach in the presence of missing data in an optimal control problem.

Inverse ProblemsVol. 41(8)
Austrian Academy of Sciences (AT), University of Graz (AT), Koblenz University of Applied Sciences (DE), Johann Radon Institute for Computational and Applied Mathematics (AT)
Openalex Percentile: Top 76%
Color perception and design
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