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PreprintCC BY 4.0HAL

Douglas-Rachford splitting method for nonconvex stochastic optimal control

  • François Caffier
  • Paul Malisani
  • Laurent Pfeiffer
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Abstract

Motivated by the numerical resolution of stochastic optimal control problems, particularly those involving nonlinear dynamics, we investigate the convergence properties of the Douglas-Rachford splitting algorithm in a nonconvex and infinite-dimensional setting. We introduce an extension of the method that applies when one component of the objective function is continuously differentiable with a locally Lipschitz gradient, while the other is weakly lower semicontinuous with a bounded domain.

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Cite

BibTeXRIS
BibTeX
@misc{caffier2026douglasrachford,
  title = {{Douglas-Rachford splitting method for nonconvex stochastic optimal control}},
  author = {François Caffier and Paul Malisani and Laurent Pfeiffer},
  howpublished = {HAL},
  year = {2026},
  month = jul,
  doi = {10.48550/arxiv.2610.31502},
  eprint = {2610.31502},
  archivePrefix = {arXiv},
  url = {https://hal.science/hal-05835631v1},
  note = {CC BY 4.0},
}
RIS
TY  - UNPB
TI  - Douglas-Rachford splitting method for nonconvex stochastic optimal control
AU  - François Caffier
AU  - Paul Malisani
AU  - Laurent Pfeiffer
PY  - 2026
DA  - 2026/07/09
PB  - HAL
DO  - 10.48550/arxiv.2610.31502
UR  - https://hal.science/hal-05835631v1
AB  - Motivated by the numerical resolution of stochastic optimal control problems, particularly those involving nonlinear dynamics, we investigate the convergence properties of the Douglas-Rachford splitting algorithm in a nonconvex and infinite-dimensional setting. We introduce an extension of the method that applies when one component of the objective function is continuously differentiable with a locally Lipschitz gradient, while the other is weakly lower semicontinuous with a bounded domain.
ER  -