No. 2024.04
Consensus-based algorithms for stochastic optimization problems
S. Bonandin and M. Herty
Subject: Mean-field limit, particle swarm optimization, random optimization problems
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.
Reference
SIAM J. Optim. 35 (2025), no. 4, 2572-2598