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SSRN Electronic Journal
Article . 2004 . Peer-reviewed
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Efficient Line Searching for Convex Functions

Authors: Boef, E. den; Hertog, D. den;

Efficient Line Searching for Convex Functions

Abstract

In this paper we propose two new line search methods for convex functions. These new methods exploit the convexity property of the function, contrary to existing methods.The worst method is an improved version of the golden section method.For the second method it is proven that after two evaluations the objective gap is at least halved.The practical efficiency of the methods is shown by applying our methods to a real-life bus and buffer size optimization problem and to several classes of convex functions.

Country
Netherlands
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Keywords

convex optimization, convex optimization; golden section; line search., line search., convex optimization;golden section;line search., golden section

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    popularity
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    influence
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selected citations
These citations are derived from selected sources.
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!
2
Average
Average
Average
bronze
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