License: Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported license (CC BY-NC-ND 3.0)
When quoting this document, please refer to the following
DOI: 10.4230/LIPIcs.FSTTCS.2008.1767
URN: urn:nbn:de:0030-drops-17676
URL: http://dagstuhl.sunsite.rwth-aachen.de/volltexte/2008/1767/
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Feige, Uriel

On Estimation Algorithms vs Approximation Algorithms

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08004.FeigeUriel.1767.pdf (0.4 MB)

Abstract

In a combinatorial optimization problem, when given an input
instance, one seeks a feasible solution that optimizes the value
of the objective function. Many combinatorial optimization
problems are NP-hard. A way of coping with NP-hardness is by
considering approximation algorithms. These algorithms run in
polynomial time, and their performance is measured by their
approximation ratio: the worst case ratio between the value of the
solution produced and the value of the (unknown) optimal solution.

In some cases the design of approximation algorithms includes a
nonconstructive component. As a result, the algorithms become
estimation algorithms rather than approximation algorithms: they
allow one to estimate the value of the optimal solution, without
actually producing a solution whose value is close to optimal.

We shall present a few such examples, and discuss some open
questions.

BibTeX - Entry

@InProceedings{feige:LIPIcs:2008:1767,
  author =	{Uriel Feige},
  title =	{{On Estimation Algorithms vs Approximation Algorithms}},
  booktitle =	{IARCS Annual Conference on Foundations of Software Technology and Theoretical Computer Science},
  pages =	{357--363},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-939897-08-8},
  ISSN =	{1868-8969},
  year =	{2008},
  volume =	{2},
  editor =	{Ramesh Hariharan and Madhavan Mukund and V Vinay},
  publisher =	{Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{http://drops.dagstuhl.de/opus/volltexte/2008/1767},
  URN =		{urn:nbn:de:0030-drops-17676},
  doi =		{10.4230/LIPIcs.FSTTCS.2008.1767},
  annote =	{Keywords: Estimation Algorithms, Approximation Algorithms, Combinatorial Optimization}
}

Keywords: Estimation Algorithms, Approximation Algorithms, Combinatorial Optimization
Collection: IARCS Annual Conference on Foundations of Software Technology and Theoretical Computer Science
Issue Date: 2008
Date of publication: 05.12.2008

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