Approximating the Lovász θ function with the subgradient method

Giandomenico, Monia and Letchford, Adam N. and Rossi, Fabrizio and Smriglio, Stefano (2013) Approximating the Lovász θ function with the subgradient method. Electronic Notes in Discrete Mathematics, 41. pp. 157-164. ISSN 1571-0653

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Abstract

The famous Lovász theta number θ(G) is expressed as the optimal solution of a semidefinite program. As such, it can be computed in polynomial time to an arbitrary precision. Nevertheless, computing it in practice yields some difficulties as the size of the graph gets larger and larger, despite recent significant advances of semidefinite programming (SDP) solvers. We present a way around SDP which exploits a well-known equivalence between SDP and lagrangian relaxations of non-convex quadratic programs. This allows us to design a subgradient algorithm which is shown to be competitive with SDP algorithms in terms of efficiency, while being preferable as far as memory requirements, flexibility and stability are concerned.

Item Type:
Journal Article
Journal or Publication Title:
Electronic Notes in Discrete Mathematics
Uncontrolled Keywords:
/dk/atira/pure/subjectarea/asjc/2600/2607
Subjects:
?? lagrangian relaxationmaximum stable setquadratic programmingsubgradient methoddiscrete mathematics and combinatoricsapplied mathematics ??
ID Code:
206762
Deposited By:
Deposited On:
12 Oct 2023 10:55
Refereed?:
Yes
Published?:
Published
Last Modified:
16 Jul 2024 00:21