A consensus-based model for global optimization and its mean-field limit

R. Pinnau, C. Totzeck, O. Tse, S. Martin

Research output: Contribution to journalArticleAcademicpeer-review

18 Citations (Scopus)
1 Downloads (Pure)

Abstract


We introduce a novel first-order stochastic swarm intelligence (SI) model in the spirit of consensus formation models, namely a consensus-based optimization (CBO) algorithm, which may be used for the global optimization of a function in multiple dimensions. The CBO algorithm allows for passage to the mean-field limit, which results in a nonstandard, nonlocal, degenerate parabolic partial differential equation (PDE). Exploiting tools from PDE analysis we provide convergence results that help to understand the asymptotic behavior of the SI model. We further present numerical investigations underlining the feasibility of our approach.


Original languageEnglish
Pages (from-to)183-204
Number of pages22
JournalMathematical Models & Methods in Applied Sciences
Volume27
Issue number1
DOIs
Publication statusPublished - 2017

Keywords

  • Consensus formation
  • global optimization
  • interacting system
  • mean-field limit
  • stochastic differential equations

Fingerprint Dive into the research topics of 'A consensus-based model for global optimization and its mean-field limit'. Together they form a unique fingerprint.

Cite this