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: http://dagstuhl.sunsite.rwth-aachen.de/volltexte/2008/1753/
Golovin, Daniel ;
Gupta, Anupam ;
Kumar, Amit ;
Tangwongsan, Kanat
All-Norms and All-L_p-Norms Approximation Algorithms
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 |