In this paper, we provide an analytical framework for investigating the efficiency of a consensus-based model for tackling global optimization problems. This work justifies the optimization algorithm in the mean-field sense showing the convergence to the global minimizer for a large class of functions. Theoretical results on consensus estimates are then illustrated by numerical simulations where variants of the method including nonlinear diffusion are introduced.
|Journal||Mathematical Models and Methods in Applied Sciences|
|Publication status||Published - 2018 Jun 15|
All Science Journal Classification (ASJC) codes
- Modelling and Simulation
- Applied Mathematics