An analytical framework for a consensus-based global optimization method
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Author(s)
Carrillo de la Plata, J
Choi, Young-Pil
Totzeck, Claudia
Tse, Oliver
Type
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.
Read More: https://www.worldscientific.com/doi/abs/10.1142/S0218202518500276
Read More: https://www.worldscientific.com/doi/abs/10.1142/S0218202518500276
Date Issued
2018-06-15
Date Acceptance
2018-01-15
Citation
Mathematical Models and Methods in Applied Sciences, 2018, 28 (06), pp.1037-1066
ISSN
1793-6314
Publisher
World Scientific Publishing
Start Page
1037
End Page
1066
Journal / Book Title
Mathematical Models and Methods in Applied Sciences
Volume
28
Issue
06
Copyright Statement
© 2018 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.
of this work is permitted, provided the original work is properly cited.
Sponsor
Engineering & Physical Science Research Council (EPSRC)
Grant Number
EP/P031587/1
Subjects
0102 Applied Mathematics
Applied Mathematics
Publication Status
Published
Date Publish Online
2018-04-11