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Meta-optimization of dimension adaptive parameter schema for Nelder–Mead algorithm in high-dimensional problems
ID
Rojec, Žiga
(
Author
),
ID
Tuma, Tadej
(
Author
),
ID
Olenšek, Jernej
(
Author
),
ID
Bürmen, Arpad
(
Author
),
ID
Puhan, Janez
(
Author
)
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MD5: 2DDBCF5693A6C2276E350BDB5E9279EF
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https://www.mdpi.com/2227-7390/10/13/2288
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Abstract
Although proposed more than half a century ago, the Nelder–Mead simplex search algorithm is still widely used. Four numeric constants define the operations and behavior of the algorithm. The algorithm with the original constant values performs fine on most low-dimensional, but poorly on high-dimensional, problems. Therefore, to improve its behavior in high dimensions, several adaptive schemas setting the constants according to the problem dimension were proposed in the past. In this work, we present a novel adaptive schema obtained by a meta-optimization procedure. We describe a schema candidate with eight parameters subject to meta-optimization and define an objective function evaluating the candidate’s performance. The schema is optimized on up to 100-dimensional problems using the Parallel Simulated Annealing with Differential Evolution global method. The obtained global minimum represents the proposed schema. We compare the performance of the optimized schema with the existing adaptive schemas. The data profiles on the Gao–Han modified quadratic, Moré–Garbow–Hilstrom, and CUTEr (Constrained and Unconstrained Testing Environment, revisited) benchmark problem sets show that the obtained schema outperforms the existing adaptive schemas in terms of accuracy and convergence speed.
Language:
English
Keywords:
meta-optimization
,
Nelder-Mead algorithm
,
adaptive parameter schema
,
high-dimensional optimization problems
Work type:
Article
Typology:
1.01 - Original Scientific Article
Organization:
FE - Faculty of Electrical Engineering
Publication status:
Published
Publication version:
Version of Record
Year:
2022
Number of pages:
16 str.
Numbering:
Vol. 10, iss. 13, art. 2288
PID:
20.500.12556/RUL-145174
UDC:
004
ISSN on article:
2227-7390
DOI:
10.3390/math10132288
COBISS.SI-ID:
118971139
Publication date in RUL:
12.04.2023
Views:
568
Downloads:
76
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Record is a part of a journal
Title:
Mathematics
Shortened title:
Mathematics
Publisher:
MDPI AG
ISSN:
2227-7390
COBISS.SI-ID:
523267865
Licences
License:
CC BY 4.0, Creative Commons Attribution 4.0 International
Link:
http://creativecommons.org/licenses/by/4.0/
Description:
This is the standard Creative Commons license that gives others maximum freedom to do what they want with the work as long as they credit the author.
Secondary language
Language:
Slovenian
Keywords:
metaoptimizacija
,
algoritem Nelder-Mead
,
adaptivni parametri
,
visokodimenzionalni optimizacijski problemi
Projects
Funder:
ARRS - Slovenian Research Agency
Project number:
P2-0246
Name:
ICT4QoL - Informacijsko komunikacijske tehnologije za kakovostno življenje
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