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Moreau–Yosida regularization in shape optimization with geometric constraints


In the context of shape optimization with geometric constraints we employ the method of mappings (perturbation of identity) to obtain an optimal control problem with a nonlinear state equation on a fixed reference domain. The Lagrange multiplier associated with the geometric shape constraint has a low regularity (similar to state constrained problems), which we circumvent by penalization and a continuation scheme. We employ a Moreau–Yosida-type regularization and assume a second-order condition to hold. The regularized problems can then be solved with a semismooth Newton method and we study the properties of the regularized solutions and the rate of convergence towards a solution of the original problem. A model for the value function in the spirit of Hintermüller and Kunisch (SIAM J Control Optim 45(4): 1198–1221, 2006) is introduced and used in an update strategy for the regularization parameter. The theoretical findings are supported by numerical tests.

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We gratefully acknowledge support from the International Research Training Group IGDK1754, funded by the German Science Foundation (DFG).

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Correspondence to Moritz Keuthen.

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Keuthen, M., Ulbrich, M. Moreau–Yosida regularization in shape optimization with geometric constraints. Comput Optim Appl 62, 181–216 (2015).

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  • Shape optimization
  • Moreau–Yosida regularization
  • Method of mappings
  • Semismooth newton
  • Geometric constraints