Consensus-based Optimization and Ensemble Kalman Inversion for Global Optimization Problems with Constraints - Archive ouverte HAL
Chapitre D'ouvrage Année : 2023

Consensus-based Optimization and Ensemble Kalman Inversion for Global Optimization Problems with Constraints

Résumé

We introduce a practical method for incorporating equality and inequality constraints in global optimization methods based on stochastic interacting particle systems, specifically consensus-based optimization (CBO) and ensemble Kalman inversion (EKI). Unlike other approaches in the literature, the method we propose does not constrain the dynamics to the feasible region of the state space at all times; the particles evolve in the full space, but are attracted towards the feasible set by means of a penalization term added to the objective function and, in the case of CBO, an additional relaxation drift. We study the properties of the method through the associated mean-field Fokker--Planck equation and demonstrate its performance in numerical experiments on several test problems.

Dates et versions

hal-03425989 , version 1 (11-11-2021)

Identifiants

Citer

José Antonio Carrillo, Claudia Totzeck, Urbain Vaes. Consensus-based Optimization and Ensemble Kalman Inversion for Global Optimization Problems with Constraints. Modeling and Simulation for Collective Dynamics, 40, WORLD SCIENTIFIC, pp.195-230, 2023, Lecture Notes Series, Institute for Mathematical Sciences, National University of Singapore, ⟨10.1142/9789811266140_0004⟩. ⟨hal-03425989⟩
66 Consultations
0 Téléchargements

Altmetric

Partager

More