Data error analysis in unconstrained optimization problems with the CESTAC method
type: Item
instance of: scholarly article
title: Data error analysis in unconstrained optimization problems with the CESTAC method
zbMATH Open document ID: 0669.65049
DOI: 10.1016/0378-4754(88)90074-2
author: Nicole Alliot
published in: Mathematics and Computers in Simulation
publication date: 1988-01-01T00:00:00Z
review text: This paper is concerned with the solution of optimization problems that depend on inexact data from a known distribution: how does the solution depend on the data? A method to estimate mean and standard deviation of the distribution of the solution is proposed. This method is about three times as expensive as a single optimization. The algorithm is described and a simple example is considered.
Mathematics Subject Classification ID: 65K05
Mathematics Subject Classification ID: 90C15
Mathematics Subject Classification ID: 90C30
zbMATH DE Number: 4096703
zbMATH Keywords: CESTAC method
zbMATH Keywords: unconstrained optimization
zbMATH Keywords: numerical example
zbMATH Keywords: inexact data
zbMATH Keywords: mean
zbMATH Keywords: standard deviation
zbMATH Keywords: distribution of the solution
reviewed by: Thomas F. Coleman
MaRDI profile type: Publication
full work available at URL: 0378-4754(88)90074-2
OpenAlex ID: W2067220435
cites work: Q5732992
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description: scientific article; zbMATH DE number 4096703