An analytical framework for consensus-based global optimization method

被引：85

作者：

Carrillo, Jose A. ^{[1
]}

Choi, Young-Pil ^{[2
,3
]}

Totzeck, Claudia ^{[4
]}

Tse, Oliver ^{[5
]}

机构：

[1] Imperial Coll London, Dept Math, London SW7 2AZ, England

[2] Inha Univ, Dept Math, Incheon 402751, South Korea

[3] Inha Univ, Inst Appl Math, Incheon 402751, South Korea

[4] Tech Univ Kaiserslautern, Dept Math, Erwin Schrodinger Str, D-67663 Kaiserslautern, Germany

[5] Eindhoven Univ Technol, Dept Math & Comp Sci, POB 513, NL-5600 MB Eindhoven, Netherlands

来源：

MATHEMATICAL MODELS & METHODS IN APPLIED SCIENCES | 2018年 / 28卷 / 06期

基金：

英国工程与自然科学研究理事会;

关键词：

Global optimization; opinion dynamics; consensus formation; agent-based models; stochastic dynamics; mean-field limit; FLOCK SOLUTIONS; PARTICLE; METAHEURISTICS; DYNAMICS; MODELS;

D O I：

10.1142/S0218202518500276

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

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.

引用

页码：1037 / 1066

页数：30

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