Consistency of Sample-Based Stationary Points for Infinite-Dimensional Stochastic Optimization
Year: 2025
Type: article
Abstract: . We consider stochastic optimization problems with possibly nonsmooth integrands posed in infinite-dimensional decision spaces and approximate these stochastic programs via a sample-based approaches. We establish the asymptotic consistency of approximate Clarke stationary points of the sample-based approximations. Our framework is applied to risk-averse semilinear PDE-constrained optimization using the average value-at-risk and risk-neutral bilinear PDE-constrained optimization.
Source: SIAM Journal on Optimization
DOI: 10.1137/23m1600608
Author: Johannes Milz
Institution: Georgia Institute of Technology
Language: English
Field: Decision Sciences
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W4406038144