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Numerical Algorithms for the Parametric Continuation of Stiff ODEs Deriving from the Modeling of Combustion with Detailed Chemical Mechanisms Read chapter Read first chapter

2020 | OriginalPaper | Chapter

On Acceleration of Derivative-Free Univariate Lipschitz Global Optimization Methods

Authors : Dmitri E. Kvasov, Marat S. Mukhametzhanov, Maria Chiara Nasso, Yaroslav D. Sergeyev

Published in: Numerical Computations: Theory and Algorithms

Publisher: Springer International Publishing

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Abstract

Univariate box-constrained global optimization problems are considered, where the objective function is supposed to be Lipschitz continuous and multiextremal. It is assumed that its analytical representation is unknown (the function is given as a “black-box”) and even one its evaluation is a computationally expensive procedure. Geometric and information statistical frameworks for construction of global optimization algorithms are discussed. Several powerful acceleration techniques are described and a number of methods of both classes is constructed by mixing the introduced acceleration ideas. Numerical experiments executed on broad test classes taken from the literature show advantages of the presented techniques with respect to their direct competitors.

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previous chapter On a Comparison of Several Numerical Integration Methods for Ordinary Systems of Differential Equations
next chapter Numerical Simulation of Ski-Jump Hydraulic Behavior
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Metadata
Title
On Acceleration of Derivative-Free Univariate Lipschitz Global Optimization Methods
Authors
Dmitri E. Kvasov
Marat S. Mukhametzhanov
Maria Chiara Nasso
Yaroslav D. Sergeyev
Copyright Year
2020
Book
Numerical Computations: Theory and Algorithms

Print ISBN: 978-3-030-40615-8

Electronic ISBN: 978-3-030-40616-5

Copyright Year: 2020

DOI
https://doi.org/10.1007/978-3-030-40616-5_38

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