Consensus-based algorithms for stochastic optimization problems
Optimization and Control
2025-11-24 v4
Abstract
We address an optimization problem where the cost function is the expectation of a random mapping. To tackle the problem two approaches based on the approximation of the objective function by consensus-based particle optimization methods on the search space are developed. The resulting methods are mathematically analyzed using a mean-field approximation and their connection is established. Several numerical experiments show the validity of the proposed algorithms and investigate their rates of convergence.
Cite
@article{arxiv.2404.10372,
title = {Consensus-based algorithms for stochastic optimization problems},
author = {Sabrina Bonandin and Michael Herty},
journal= {arXiv preprint arXiv:2404.10372},
year = {2025}
}