Adaptive approximation models in optimization
type: Item
instance of: scholarly article
title: Adaptive approximation models in optimization
zbMATH Open document ID: 0848.49003
DOI: 10.1007/BF02367751
author: A. N. Voronin
published in: Cybernetics and Systems Analysis
publication date: 1996-10-28T00:00:00Z
review text: In the paper a method for optimization of functions of several variables that substantially reduces the number of objective function evaluations compared with traditional methods is introduced. The method is based on the property of iterative refinement of approximation models of the optimized function in the approximation domains that contract to the extremum point. The proposed method does not require subjective specification of the starting point, steplength, or the parameters of the search procedure. The method is designed for efficient optimization of unimodal functions of several (in the practice not more than 10-15) variables and can be applied to find the global extremum of polymodal functions and also for optimization of scalarized forms of various vector objective functions.
Mathematics Subject Classification ID: 49J05
Mathematics Subject Classification ID: 49J27
Mathematics Subject Classification ID: 93C40
zbMATH DE Number: 830651
zbMATH Keywords: extremum points
zbMATH Keywords: adaptive approximation
zbMATH Keywords: optimization
zbMATH Keywords: iterative refinement
zbMATH Keywords: vector objective functions
MaRDI profile type: Publication
cites work: Q3818927
cites work: Paths, Trees, and Flowers
cites work: Global optimization using interval analysis - the multi-dimensional case
cites work: Q4005363
full work available at URL: https://doi.org/10.1007/bf02367751
OpenAlex ID: W2009340250
description: scientific article; zbMATH DE number 830651