An analytical framework for consensus-based global optimization method

Journal article

Abstract:: 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.

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Publisher:: World Scientific Publishing
Journal:: Mathematical Models and Methods in Applied Sciences More from this journal
Volume:: 28
Issue:: 6
Pages:: 1037-1066
Publication date:: 2018-04-11
Acceptance date:: 2018-01-13
DOI:: 10.1142/S0218202518500276
EISSN:: 1793-6314
ISSN:: 0218-2025

Language:: English
Keywords:: stochastic dynamics

FFR

opinion dynamics

global optimization

mean-field limit

agent-based models

consensus formation
Pubs id:: 1098247
Local pid:: pubs:1098247
Deposit date:: 2020-04-07

Copyright holder:: Carrillo et al.
Rights statement:: © The Author(s). This is an Open Access article published by World Scientific Publishing Company. It is distributed under the terms of the Creative Commons Attribution 4.0 (CC-BY) License. Further distribution of this work is permitted, provided the original work is properly cited.

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