Improved Nelder-Mead algorithm in high dimensions with adaptive parameters based on Chebyshev spacing points

In spite of being one of the most popular optimization methods, Nelder-Mead's simplex search algorithm with the default choice of parameters performs poorly on high-dimensional problems. The work presented here concerns such values of the Nelder-Mead algorithm's parameters that help improv...

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Bibliographic Details

Published in:	Engineering optimization Vol. 52; no. 10; pp. 1814 - 1828
Main Author:	Mehta, V.K.
Format:	Journal Article
Language:	English
Published:	Abingdon Taylor & Francis 02.10.2020 Taylor & Francis Ltd
Subjects:	Adaptive algorithms adaptive parameters Algorithms Chebyshev approximation Chebyshev spacing points convergence high-dimensional problems Nelder-Mead algorithm Optimization Parameters Search algorithms
ISSN:	0305-215X, 1029-0273
Online Access:	Get full text
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