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[BR08] A Deterministic Approximation Algorithm for the Densest k-Subgraph ProblemRevue Internationale avec comité de lecture : Journal International Journal of Operational Research, vol. 3(3), pp. 301-314, 2008, (doi:10.1504/IJOR.2008.017534)Mots clés: Densest k-Subgraph Problem ; Approximation algorithms ; Detreministic ; Linear programming
Résumé:
In the Densest k-Subgraph problem (DSP), we are given an
undirected weighted graph G=(V,E) with n vertices
v1,...,vn. We seek to find a subset of k
vertices (k belonging to {1,...,n}) which maximizes the number
of edges which have their two endpoints in the subset. This problem
is NP-hard even for bipartite graphs, and no polynomial-time
algorithm with a fixed performance guarantee is known for the
general case. Several authors have proposed randomized approximation
algorithms for particular cases (especially when k=n/c,
c>1). But derandomization techniques are not easy to apply here
because of the cardinality constraint, and can have a high
computational cost. In this paper we present a deterministic
max(d,8/9c)-approximation algorithm for the
Densest k-Subgraph Problem (where d is the density of
G). The complexity of our algorithm is only the one of linear
programming. This result is obtained by using particular optimal
solutions of a linear program associated with the classical 0-1
quadratic formulation of DSP.
Equipe:
oc
Collaboration:
LIPN
BibTeX
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