An Adaptive Univariate Global Optimization Algorithm and Its Convergence Rate for Twice Continuously Differentiable Functions

James M. Calvin, Yvonne Chen, Antanas Žilinskas

Research output: Contribution to journalArticlepeer-review

11 Scopus citations

Abstract

We describe an adaptive algorithm for approximating the global minimum of a continuous univariate function. The convergence rate of the error is studied for the case of a twice continuously differentiable function.

Original languageEnglish (US)
Pages (from-to)628-636
Number of pages9
JournalJournal of Optimization Theory and Applications
Volume155
Issue number2
DOIs
StatePublished - Nov 2012

All Science Journal Classification (ASJC) codes

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

Keywords

  • Convergence
  • Optimization
  • Statistical models

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