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One-Dimensional global optimization for observations with noise

✍ Scribed by J.M. Calvin; A. ſilinskas

Publisher
Elsevier Science
Year
2005
Tongue
English
Weight
643 KB
Volume
50
Category
Article
ISSN
0898-1221

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✦ Synopsis

A problem of one-dlmenstonal global optlmmatlon m 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 Gausslan noise. An asymptotic bound for the average error ]s estimated for the nonadaptive strategy defined by a umform grid Experimental results consistent with the asymptotic results are presented. An adaptlve algorithm is proposed and experimentally compared with the nonadaptwe strategy with respect to the average error ~) 2005 Elsevmr Ltd All rights reserved

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