Approximability of partitioning graphs with supply and demand

Takehiro Ito, Erik D. Demaine, Xiao Zhou, Takao Nishizeki

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

3 Citations (Scopus)

Abstract

Suppose that each vertex of a graph G is either a supply vertex or a demand vertex and is assigned a positive real number, called the supply or the demand. Each demand vertex can receive "power" from at most one supply vertex through edges in G. One thus wishes to partition G into connected components so that each component C either has no supply vertex or has exactly one supply vertex whose supply is at least the sum of demands in C, and wishes to maximize the fulfillment, that is, the sum of demands in all components with supply vertices. This maximization problem is known to be NP-hard even for trees having exactly one supply vertex and strongly NP-hard for general graphs. In this paper, we focus on the approximability of the problem. We first show that the problem is MAXSNP-hard and hence there is no polynomial-time approximation scheme (PTAS) for general graphs unless P=NP. We then present a fully polynomial-time approximation scheme (FPTAS) for series-parallel graphs having exactly one supply vertex. The FPTAS can be easily extended for partial k-trees, that is, graphs with bounded treewidth.

Original languageEnglish
Title of host publicationAlgorithms and Computation - 17th International Symposium, ISAAC 2006, Proceedings
Pages121-130
Number of pages10
DOIs
Publication statusPublished - 2006 Dec 1
Event17th International Symposium on Algorithms and Computation, ISAAC 2006 - Kolkata, India
Duration: 2006 Dec 182006 Dec 20

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4288 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other17th International Symposium on Algorithms and Computation, ISAAC 2006
Country/TerritoryIndia
CityKolkata
Period06/12/1806/12/20

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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