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PDE-constrained optimization

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PDE-constrained optimization is a subset of mathematical optimization where at least one of the constraints may be expressed as a partial differential equation.[1] Typical domains where these problems arise are in optimal design, optimal control, and inverse problems.[2]

Closed-form solutions are generally unavailable for PDE-constrained optimization problems, necessitating the development of numerical methods.[3][4][5] A standard formulation of PDE-constrained optimization encountered in a number of problems takes the form:[6]where in the control variable and is the Euclidean norm.

Applications

Example: 2D Navier-Stokes problem

This example problem aims to minimize the norm of the vorticity over a given 2D region with some multivariate control :[12]where the dynamics are governed by the steady, incompressible Navier-Stokes equations:

See also

References

  1. ^ Leugering, Günter; Benner, Peter; Engell, Sebastian; Griewank, Andreas; Harbrecht, Helmut; Hinze, Michael; Rannacher, Rolf; Ulbrich, Stefan, eds. (2014). "Trends in PDE Constrained Optimization". International Series of Numerical Mathematics. Springer. doi:10.1007/978-3-319-05083-6. ISSN 0373-3149.
  2. ^ Choi, Youngsoo (2011). "PDE-constrained Optimization and Beyond" (PDF). Stanford University.{{cite web}}: CS1 maint: url-status (link)
  3. ^ Biros, George; Ghattas, Omar (2005-01-01). "Parallel Lagrange--Newton--Krylov--Schur Methods for PDE-Constrained Optimization. Part I: The Krylov--Schur Solver". SIAM Journal on Scientific Computing. 27 (2): 687–713. doi:10.1137/S106482750241565X. ISSN 1064-8275.
  4. ^ Antil, Harbir; Heinkenschloss, Matthias; Hoppe, Ronald H. W.; Sorensen, Danny C. (2010-08-01). "Domain decomposition and model reduction for the numerical solution of PDE constrained optimization problems with localized optimization variables". Computing and Visualization in Science. 13 (6): 249–264. doi:10.1007/s00791-010-0142-4. ISSN 1433-0369.
  5. ^ Schöberl, Joachim; Zulehner, Walter (2007-01-01). "Symmetric Indefinite Preconditioners for Saddle Point Problems with Applications to PDE-Constrained Optimization Problems". SIAM Journal on Matrix Analysis and Applications. 29 (3): 752–773. doi:10.1137/060660977. ISSN 0895-4798.
  6. ^ Pearson, John (May 16, 2018). "PDE-Constrained Optimization in Physics, Chemistry & Biology: Modelling and Numerical Methods" (PDF). University of Edinburgh.{{cite web}}: CS1 maint: url-status (link)
  7. ^ Jameson, Antony (2003). "Aerodynamic Shape Optimization Using the Adjoint Method" (PDF). Stanford University.{{cite web}}: CS1 maint: url-status (link)
  8. ^ Hazra, S. B.; Schulz, V.; Brezillon, J.; Gauger, N. R. (2005-03-20). "Aerodynamic shape optimization using simultaneous pseudo-timestepping". Journal of Computational Physics. 204 (1): 46–64. doi:10.1016/j.jcp.2004.10.007. ISSN 0021-9991.
  9. ^ Somayaji, Mahadevabharath R.; Xenos, Michalis; Zhang, Libin; Mekarski, Megan; Linninger, Andreas A. (2008-01-01). "Systematic design of drug delivery therapies". Computers & Chemical Engineering. Process Systems Engineering: Contributions on the State-of-the-Art. 32 (1): 89–98. doi:10.1016/j.compchemeng.2007.06.014. ISSN 0098-1354.
  10. ^ Antil, Harbir; Nochetto, Ricardo H.; Venegas, Pablo (2017-10-19). "Optimizing the Kelvin force in a moving target subdomain". Mathematical Models and Methods in Applied Sciences. 28 (01): 95–130. doi:10.1142/S0218202518500033. ISSN 0218-2025.
  11. ^ Egger, Herbert; Engl, Heinz W. (2005). "Tikhonov regularization applied to the inverse problem of option pricing: convergence analysis and rates". Inverse Problems. 21 (3): 1027–1045.
  12. ^ Ridzal, Denis (2006). "Trust Region SQP Methods With Inexact Linear System Solves For Large-Scale Optimization". Rice University.{{cite web}}: CS1 maint: url-status (link)

Further reading