On the asymptotic tractability of global optimization

James M. Calvin

doi:10.1007/978-3-319-29975-4_1

On the asymptotic tractability of global optimization

James M. Calvin

Computer Science

Research output: Contribution to journal › Article › peer-review

1 Scopus citations

Abstract

We consider the intrinsic difficulty of global optimization in high dimensional Euclidean space. We adopt an asymptotic analysis, and give a lower bound on the number of function evaluations required to obtain a given error tolerance. This lower bound complements upper bounds provided by recently proposed algorithms.

Original language	English (US)
Pages (from-to)	3-12
Number of pages	10
Journal	Springer Optimization and Its Applications
Volume	107
DOIs	https://doi.org/10.1007/978-3-319-29975-4_1
State	Published - 2016

All Science Journal Classification (ASJC) codes

Control and Optimization

Keywords

Adaptive algorithms
Lower complexity bounds
Tractability

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10.1007/978-3-319-29975-4_1

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title = "On the asymptotic tractability of global optimization",

abstract = "We consider the intrinsic difficulty of global optimization in high dimensional Euclidean space. We adopt an asymptotic analysis, and give a lower bound on the number of function evaluations required to obtain a given error tolerance. This lower bound complements upper bounds provided by recently proposed algorithms.",

keywords = "Adaptive algorithms, Lower complexity bounds, Tractability",

author = "Calvin, \{James M.\}",

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KW - Adaptive algorithms

KW - Lower complexity bounds

KW - Tractability

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UR - https://www.scopus.com/pages/publications/84994496468#tab=citedBy

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JO - Springer Optimization and Its Applications

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ER -

On the asymptotic tractability of global optimization

Abstract

All Science Journal Classification (ASJC) codes

Keywords

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