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.2008.1753
URN: urn:nbn:de:0030-drops-17537
URL: https://drops.dagstuhl.de/opus/volltexte/2008/1753/
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### All-Norms and All-L_p-Norms Approximation Algorithms

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### Abstract

In many optimization problems, a solution can be viewed as ascribing
a cost\'\' to each client, and the goal is to optimize some
aggregation of the per-client costs. We often optimize some
$L_p$-norm (or some other symmetric convex function or norm) of the
vector of costs---though different applications may suggest
different norms to use. Ideally, we could obtain a solution that
optimizes several norms simultaneously.
In this paper, we examine approximation algorithms that
simultaneously perform well on all norms, or on all $L_p$ norms.

A natural problem in this framework is the $L_p$ Set Cover
problem, which generalizes \textsc{Set Cover} and \textsc{Min-Sum Set
Cover}. We show that the greedy algorithm \emph{simultaneously
gives a $(p + \ln p + O(1))$-approximation for all $p$, and show
that this approximation ratio is optimal up to constants} under
reasonable complexity-theoretic assumptions.

We additionally show how to use our analysis techniques
to give similar results for the more general \emph{submodular set
cover}, and prove some results for the so-called \emph{pipelined set
cover} problem.

We then go on to examine approximation algorithms in the
all-norms\'\' and the all-$L_p$-norms\'\' frameworks more broadly,
and present algorithms and structural results for other problems
such as $k$-facility-location, TSP, and average flow-time
minimization, extending and unifying previously
known results.

### BibTeX - Entry

@InProceedings{golovin_et_al:LIPIcs:2008:1753,
author =	{Daniel Golovin and Anupam Gupta and Amit Kumar and Kanat Tangwongsan},
title =	{{All-Norms and All-L_p-Norms Approximation Algorithms}},
booktitle =	{IARCS Annual Conference on Foundations of Software Technology and Theoretical Computer Science},
pages =	{199--210},
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/2008/1753},
URN =		{urn:nbn:de:0030-drops-17537},
doi =		{10.4230/LIPIcs.FSTTCS.2008.1753},
annote =	{Keywords: Approximation algorithms, set-cover problems, combinatorial optimization, sampling minkowski norms}
}


 Keywords: Approximation algorithms, set-cover problems, combinatorial optimization, sampling minkowski norms 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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