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2021 | OriginalPaper | Chapter

A Semismooth Newton Method for Regularized L q-quasinorm Sparse Optimal Control Problems

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Abstract

A semismooth Newton method (refered as DC–SSN) is proposed for the numerical solution of a class of nonconvex optimal control problems governed by linear elliptic partial differential equations. The nonconvex term in the cost functional arises from a Huber-type local regularization of the L q-quasinorm (q ∈ (0, 1)), therefore it promotes sparsity on the solution. The DC–SSN method solves the optimality system of the regularized problem resulting from the application of difference-of-convex functions programming tools.

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Literature
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Metadata
Title
A Semismooth Newton Method for Regularized L q-quasinorm Sparse Optimal Control Problems
Author
Pedro Merino
Copyright Year
2021
DOI
https://doi.org/10.1007/978-3-030-55874-1_71

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