On a Global Optimization Algorithm for Bivariate Smooth Functions

James M. Calvin, Antanas Žilinskas

Research output: Contribution to journalArticlepeer-review

6 Scopus citations


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 languageAmerican English
Pages (from-to)528-547
Number of pages20
JournalJournal of Optimization Theory and Applications
Issue number2
StatePublished - Oct 7 2014

ASJC Scopus subject areas

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


  • Convergence
  • Decision theory
  • Delaunay triangulation
  • Global optimization


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