On a Global Optimization Algorithm for Bivariate Smooth Functions

James M. Calvin, Antanas Žilinskas

Research output: Contribution to journalArticlepeer-review

6 Scopus citations

Abstract

The problem of approximating the global minimum of a function of two variables is considered. A method is proposed rooted in the statistical approach to global optimization. The proposed algorithm partitions the feasible region using a Delaunay triangulation. Only the objective function values are required by the optimization algorithm. The asymptotic convergence rate is analyzed for a class of smooth functions. Numerical examples are provided.

Original languageEnglish (US)
Pages (from-to)528-547
Number of pages20
JournalJournal of Optimization Theory and Applications
Volume163
Issue number2
DOIs
StatePublished - Oct 7 2014

All Science Journal Classification (ASJC) codes

  • Control and Optimization
  • Management Science and Operations Research
  • Applied Mathematics

Keywords

  • Convergence
  • Decision theory
  • Delaunay triangulation
  • Global optimization

Fingerprint Dive into the research topics of 'On a Global Optimization Algorithm for Bivariate Smooth Functions'. Together they form a unique fingerprint.

Cite this