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Computational Mathematics and Modeling
Article . 2001 . Peer-reviewed
License: Springer Nature TDM
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Some Issues in the Theory of Optimal Algorithms and Informational Complexity

Some issues in the theory of optimal algorithms and informational complexity
descriptionPublicationkeyboard_double_arrow_right Article 01 Apr 2001 English Publisher:Springer Science and Business Media LLCJournal:Computational Mathematics and Modeling, volume 12, pages 137-156 (issn: 1046-283X, eissn: 1573-837X, Copyright policy )
Authors: Popov, N. M.;

doi: 10.1023/a:1012562132541

Some Issues in the Theory of Optimal Algorithms and Informational Complexity

Abstract

The article presents the basic concepts and reviews the main results of the theory of optimal algorithms and informational complexity. Informational complexity bounds are provided for Lipschitzian multi-criterion problems that construct the approximate Pareto-optimal strategy set under different interpretations of approximation-approximation ``by the functional'' and approximation ``by the argument.'' The informational complexity is compared for the scalar global optimization problem and the problem of finding the roots of nonlinear equations by global search methods.

Keywords

scalar global optimization problem, Complexity and performance of numerical algorithms, Analysis of algorithms and problem complexity, Lipschitzian multi-criterion problems, Algorithmic information theory (Kolmogorov complexity, etc.), informational complexity

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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