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Solving Generalized Maximum Dispersion with Linear Programming
Department of Computer Science, Washington University, USA.
Institut für Informatik, Christian-Albrechts-Universität zu Kiel, Germany .
Zentrum für Paralleles Rechnen Universität zu Köln, Germany.
2007 (English)In: Proceedings of 3rd International Conference on Algorithmic Aspects in Information and Management (AAIM 2007) / [ed] M.-Y. Kao and X.-Y. Li, Berlin-Heidelberg: Springer Berlin-Heidelberg , 2007, 1-10 p.Conference paper, Published paper (Refereed)
Abstract [en]

The Generalized Maximum Dispersion problem asks for a partition of a given graph into p vertex-disjoint sets, each of them having at most k vertices. The goal is to maximize the total edge-weight of the induced subgraphs. We present the first LP-based approximation algorithm.

Place, publisher, year, edition, pages
Berlin-Heidelberg: Springer Berlin-Heidelberg , 2007. 1-10 p.
Series
Lecture Notes in Computer Science, Volume 4508
Keyword [en]
Approximation Algorithms, Randomized Algorithms, Generalized Maximum Dispersion
National Category
Discrete Mathematics
Identifiers
URN: urn:nbn:se:umu:diva-84442OAI: oai:DiVA.org:umu-84442DiVA: diva2:684075
Conference
3rd International Conference on Algorithmic Aspects in Information and Management (AAIM 2007)
Available from: 2014-01-07 Created: 2014-01-07 Last updated: 2014-12-19Bibliographically approved

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CiteExportLink to record
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