An analytical framework for consensus-based global optimization method-Reference-Cited by-同舟云学术

An analytical framework for consensus-based global optimization method

Published:2018-05-21 Issue:06 Volume:28 Page:1037-1066
ISSN:0218-2025
Container-title:Mathematical Models and Methods in Applied Sciences
language:en
Short-container-title:Math. Models Methods Appl. Sci.

Author:

Carrillo José A.¹,Choi Young-Pil²,Totzeck Claudia³,Tse Oliver⁴

Affiliation:

1. Department of Mathematics, Imperial College London, London SW7 2AZ, UK

2. Department of Mathematics and Institute of Applied Mathematics, Inha University, Incheon 402-751, Republic of Korea

3. Department of Mathematics, Technische Universität Kaiserslautern, Erwin-Schrödinger-Strasse, 67663 Kaiserslautern, Germany

4. Department of Mathematics and Computer Science, Eindhoven University of Technology, P. O. Box 513, 5600MB Eindhoven, The Netherlands

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.

Publisher

World Scientific Pub Co Pte Lt

Subject

Applied Mathematics,Modeling and Simulation

Link

https://www.worldscientific.com/doi/pdf/10.1142/S0218202518500276

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1. Complex Adaptive Systems Modeling: A multidisciplinary Roadmap

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