A globalized inexact semismooth Newton method for strongly convex optimal control problems
Abstract
We investigate a globalized inexact semismooth Newton method applied to strongly convex optimization problems in Hilbert spaces. Here, the semismooth Newton method is appplied to the dual problem, which has a continuously differentiable objective. We prove global strong convergence of iterates as well as transition to local superlinear convergence. The latter needs a second-order Taylor expansion involving semismooth derivative concepts. The convergence of the globalized method is demonstrated in numerical examples, for which the local unglobalized method diverges.
Fields of Study & Subjects
Advanced Optimization Algorithms Research
Advanced Control Systems Optimization
Optimization and Variational Analysis
Publication details
- Journal / source
- Journal of Nonsmooth Analysis and Optimization
- Publisher
- Centre pour la Communication Scientifique Directe (CCSD)
- Volume
- Volume 6
- Issue
- Original research articles
- Publication date
- 26 March 2026
- Language
- EN