An analytical framework for a consensus-based global optimization method
José Antonio Carrillo, Choi, Y-P, Claudia Totzeck, Oliver T.C. Tse · Spiral (Imperial College London) · 2018
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. Read More: https://www.worldscientific.com/doi/abs/10.1142/S0218202518500276