An adaptive univariate global optimization algorithm and its convergence rate under the Wiener measure

Authors

James Calvin, Department of Computer Science

Document Type

Article

Publication Date

12-1-2011

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 random objective function distributed according to the Wiener measure. © 2011 Vilnius University.

Identifier

84855494782 (Scopus)

Publication Title

Informatica

ISSN

08684952

First Page

471

Last Page

488

Issue

4

Volume

22

Recommended Citation

Calvin, James, "An adaptive univariate global optimization algorithm and its convergence rate under the Wiener measure" (2011). Faculty Publications. 11004.
https://digitalcommons.njit.edu/fac_pubs/11004