Approximation algorithms for buy-at-bulk geometric network design

Artur Czumaj, Jurek Czyzowicz, Leszek Ga̧sieniec, Jesper Jansson, Andrzej Lingas, Pawel Zylinski

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

The buy-at-bulk network design problem has been extensively studied in the general graph model. In this paper we consider the geometric version of the problem, where all points in a Euclidean space are candidates for network nodes. We present the first general approach for geometric versions of basic variants of the buy-at-bulk network design problem. It enables us to obtain quasi-polynomial-time approximation schemes for basic variants of the buy-at-bulk geometric network design problem with polynomial total demand. Then, for instances with few sinks and low capacity links, we design very fast polynomial-time low-constant approximations algorithms.

Original languageEnglish (US)
Title of host publicationAlgorithms and Data Structures - 11th International Symposium, WADS 2009, Proceedings
Pages168-180
Number of pages13
DOIs
StatePublished - Sep 14 2009
Externally publishedYes
Event11th International Symposium on Algorithms and Data Structures, WADS 2009 - Banff, AB, Canada
Duration: Aug 21 2009Aug 23 2009

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume5664 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference11th International Symposium on Algorithms and Data Structures, WADS 2009
CountryCanada
CityBanff, AB
Period8/21/098/23/09

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ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Czumaj, A., Czyzowicz, J., Ga̧sieniec, L., Jansson, J., Lingas, A., & Zylinski, P. (2009). Approximation algorithms for buy-at-bulk geometric network design. In Algorithms and Data Structures - 11th International Symposium, WADS 2009, Proceedings (pp. 168-180). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5664 LNCS). https://doi.org/10.1007/978-3-642-03367-4_15