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Title: A direct search algorithm for optimization with noisy function evaluations

Abstract

In this paper we describe a new direct search algorithm, reminiscent of the Nelder-Mead method, and related to a more recent pattern search algorithm proposed by Torczon. We believe that this method has applications in situations in which each function evaluation is noisy, but in which repeated function evaluations at the same point can be used to progressively reduce the error. For example, this will occur if the objective function value is given as a result of a simulation experiment. We investigate the convergence behaviour of the new algorithm for problems in which each function evaluation returns the true value of the function plus a random error drawn from a Normal distribution.

Authors:
 [1];
  1. Univ. of Cambridge, MA (United States)
Publication Date:
OSTI Identifier:
35768
Report Number(s):
CONF-9408161-
TRN: 94:009753-0023
Resource Type:
Conference
Resource Relation:
Conference: 15. international symposium on mathematical programming, Ann Arbor, MI (United States), 15-19 Aug 1994; Other Information: PBD: 1994; Related Information: Is Part Of Mathematical programming: State of the art 1994; Birge, J.R.; Murty, K.G. [eds.]; PB: 312 p.
Country of Publication:
United States
Language:
English
Subject:
99 MATHEMATICS, COMPUTERS, INFORMATION SCIENCE, MANAGEMENT, LAW, MISCELLANEOUS; DATA BASE MANAGEMENT; INFORMATION RETRIEVAL; OPTIMIZATION; ALGORITHMS

Citation Formats

Anderson, E, and Ferris, M. A direct search algorithm for optimization with noisy function evaluations. United States: N. p., 1994. Web.
Anderson, E, & Ferris, M. A direct search algorithm for optimization with noisy function evaluations. United States.
Anderson, E, and Ferris, M. 1994. "A direct search algorithm for optimization with noisy function evaluations". United States.
@article{osti_35768,
title = {A direct search algorithm for optimization with noisy function evaluations},
author = {Anderson, E and Ferris, M},
abstractNote = {In this paper we describe a new direct search algorithm, reminiscent of the Nelder-Mead method, and related to a more recent pattern search algorithm proposed by Torczon. We believe that this method has applications in situations in which each function evaluation is noisy, but in which repeated function evaluations at the same point can be used to progressively reduce the error. For example, this will occur if the objective function value is given as a result of a simulation experiment. We investigate the convergence behaviour of the new algorithm for problems in which each function evaluation returns the true value of the function plus a random error drawn from a Normal distribution.},
doi = {},
url = {https://www.osti.gov/biblio/35768}, journal = {},
number = ,
volume = ,
place = {United States},
year = {Sat Dec 31 00:00:00 EST 1994},
month = {Sat Dec 31 00:00:00 EST 1994}
}

Conference:
Other availability
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