Robust optimization of graph partitioning involving interval uncertainty

Neng Fan, Qipeng P. Zheng, Panos M. Pardalos

Research output: Contribution to journalArticle

6 Citations (Scopus)

Abstract

The graph partitioning problem consists of partitioning the vertex set of a graph into several disjoint subsets so that the sum of weights of the edges between the disjoint subsets is minimized. In this paper, robust optimization models with two decomposition algorithms are introduced to solve the graph partitioning problem with interval uncertain weights of edges. The bipartite graph partitioning problem with edge uncertainty is also presented. Throughout this paper, we make no assumption regarding the probability of the uncertain weights.

Original languageEnglish (US)
Pages (from-to)53-61
Number of pages9
JournalTheoretical Computer Science
Volume447
DOIs
StatePublished - Aug 17 2012
Externally publishedYes

Fingerprint

Graph Partitioning
Robust Optimization
Set theory
Decomposition
Uncertainty
Interval
Disjoint
Subset
Decomposition Algorithm
Optimization Model
Bipartite Graph
Partitioning
Graph in graph theory
Vertex of a graph

Keywords

  • Benders decomposition
  • Bipartite graph partitioning
  • Graph partitioning
  • Robust optimization
  • Uncertainty

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Robust optimization of graph partitioning involving interval uncertainty. / Fan, Neng; Zheng, Qipeng P.; Pardalos, Panos M.

In: Theoretical Computer Science, Vol. 447, 17.08.2012, p. 53-61.

Research output: Contribution to journalArticle

Fan, Neng ; Zheng, Qipeng P. ; Pardalos, Panos M. / Robust optimization of graph partitioning involving interval uncertainty. In: Theoretical Computer Science. 2012 ; Vol. 447. pp. 53-61.
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