One-dimensional global optimization for observations with noise

J. M. Calvin; A. Žilinskas

doi:10.1016/j.camwa.2004.12.014

One-dimensional global optimization for observations with noise

J. M. Calvin, A. Žilinskas

Computer Science

Research output: Contribution to journal › Article › peer-review

27 Scopus citations

Abstract

A problem of one-dimensional global optimization in the presence of noise is considered. The approach is based on modeling the objective function as a standard Wiener process which is observed with independent Gaussian noise. An asymptotic bound for the average error is estimated for the nonadaptive strategy defined by a uniform grid. Experimental results consistent with the asymptotic results are presented. An adaptive algorithm is proposed and experimentally compared with the nonadaptive strategy with respect to the average error.

Original language	English (US)
Pages (from-to)	157-169
Number of pages	13
Journal	Computers and Mathematics with Applications
Volume	50
Issue number	1-2
DOIs	https://doi.org/10.1016/j.camwa.2004.12.014
State	Published - Jul 2005

All Science Journal Classification (ASJC) codes

Modeling and Simulation
Computational Theory and Mathematics
Computational Mathematics

Keywords

Optimization
Statistical models

Access to Document

10.1016/j.camwa.2004.12.014

Cite this

@article{132dd7e578da4f88815a52570f8e104e,

title = "One-dimensional global optimization for observations with noise",

abstract = "A problem of one-dimensional global optimization in the presence of noise is considered. The approach is based on modeling the objective function as a standard Wiener process which is observed with independent Gaussian noise. An asymptotic bound for the average error is estimated for the nonadaptive strategy defined by a uniform grid. Experimental results consistent with the asymptotic results are presented. An adaptive algorithm is proposed and experimentally compared with the nonadaptive strategy with respect to the average error.",

keywords = "Optimization, Statistical models",

author = "Calvin, {J. M.} and A. {\v Z}ilinskas",

note = "Funding Information: The work of the first author was supported in part by the National Scmnce Foundation under grant DMI-9900117",

year = "2005",

month = jul,

doi = "10.1016/j.camwa.2004.12.014",

language = "English (US)",

volume = "50",

pages = "157--169",

journal = "Computers and Mathematics with Applications",

issn = "0898-1221",

publisher = "Elsevier Limited",

number = "1-2",

}

TY - JOUR

T1 - One-dimensional global optimization for observations with noise

AU - Calvin, J. M.

AU - Žilinskas, A.

N1 - Funding Information: The work of the first author was supported in part by the National Scmnce Foundation under grant DMI-9900117

PY - 2005/7

Y1 - 2005/7

N2 - A problem of one-dimensional global optimization in the presence of noise is considered. The approach is based on modeling the objective function as a standard Wiener process which is observed with independent Gaussian noise. An asymptotic bound for the average error is estimated for the nonadaptive strategy defined by a uniform grid. Experimental results consistent with the asymptotic results are presented. An adaptive algorithm is proposed and experimentally compared with the nonadaptive strategy with respect to the average error.

AB - A problem of one-dimensional global optimization in the presence of noise is considered. The approach is based on modeling the objective function as a standard Wiener process which is observed with independent Gaussian noise. An asymptotic bound for the average error is estimated for the nonadaptive strategy defined by a uniform grid. Experimental results consistent with the asymptotic results are presented. An adaptive algorithm is proposed and experimentally compared with the nonadaptive strategy with respect to the average error.

KW - Optimization

KW - Statistical models

UR - http://www.scopus.com/inward/record.url?scp=27544449903&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=27544449903&partnerID=8YFLogxK

U2 - 10.1016/j.camwa.2004.12.014

DO - 10.1016/j.camwa.2004.12.014

M3 - Article

AN - SCOPUS:27544449903

SN - 0898-1221

VL - 50

SP - 157

EP - 169

JO - Computers and Mathematics with Applications

JF - Computers and Mathematics with Applications

IS - 1-2

ER -

One-dimensional global optimization for observations with noise

Abstract

All Science Journal Classification (ASJC) codes

Keywords

Access to Document

Other files and links

Fingerprint

Cite this