An inexact semismooth Newton-Krylov method for semilinear elliptic optimal control problem

Fuente: arXiv
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Auteurs principaux: Chen, Shiqi, Chen, Xuesong
Format: Preprint
Publié: 2025
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author Chen, Shiqi
Chen, Xuesong
author_facet Chen, Shiqi
Chen, Xuesong
contents An inexact semismooth Newton method has been proposed for solving semi-linear elliptic optimal control problems in this paper. This method incorporates the generalized minimal residual (GMRES) method, a type of Krylov subspace method, to solve the Newton equations and utilizes nonmonotonic line search to adjust the iteration step size. The original problem is reformulated into a nonlinear equation through variational inequality principles and discretized using a second-order finite difference scheme. By leveraging slanting differentiability, the algorithm constructs semismooth Newton directions and employs GMRES method to inexactly solve the Newton equations, significantly reducing computational overhead. A dynamic nonmonotonic line search strategy is introduced to adjust stepsizes adaptively, ensuring global convergence while overcoming local stagnation. Theoretical analysis demonstrates that the algorithm achieves superlinear convergence near optimal solutions when the residual control parameter $η_k$ approaches to 0. Numerical experiments validate the method's accuracy and efficiency in solving semilinear elliptic optimal control problems, corroborating theoretical insights.
format Preprint
id arxiv_https___arxiv_org_abs_2511_10058
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle An inexact semismooth Newton-Krylov method for semilinear elliptic optimal control problem
Chen, Shiqi
Chen, Xuesong
Optimization and Control
Numerical Analysis
49M41
An inexact semismooth Newton method has been proposed for solving semi-linear elliptic optimal control problems in this paper. This method incorporates the generalized minimal residual (GMRES) method, a type of Krylov subspace method, to solve the Newton equations and utilizes nonmonotonic line search to adjust the iteration step size. The original problem is reformulated into a nonlinear equation through variational inequality principles and discretized using a second-order finite difference scheme. By leveraging slanting differentiability, the algorithm constructs semismooth Newton directions and employs GMRES method to inexactly solve the Newton equations, significantly reducing computational overhead. A dynamic nonmonotonic line search strategy is introduced to adjust stepsizes adaptively, ensuring global convergence while overcoming local stagnation. Theoretical analysis demonstrates that the algorithm achieves superlinear convergence near optimal solutions when the residual control parameter $η_k$ approaches to 0. Numerical experiments validate the method's accuracy and efficiency in solving semilinear elliptic optimal control problems, corroborating theoretical insights.
title An inexact semismooth Newton-Krylov method for semilinear elliptic optimal control problem
topic Optimization and Control
Numerical Analysis
49M41
url https://arxiv.org/abs/2511.10058