Exploiting sparsity for the min k-partition problem

  • The minimum k-partition problem is a challenging combinatorial problem with a diverse set of applications ranging from telecommunications to sports scheduling. It generalizes the max-cut problem and has been extensively studied since the late sixties. Strong integer formulations proposed in the literature suffer from a large number of constraints and variables. In this work, we introduce two more compact integer linear and semidefinite reformulations that exploit the sparsity of the underlying graph and develop theoretical results leveraging the power of chordal decomposition. Numerical experiments show that the new formulations improve upon state-of-the-art.

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Metadaten
Author:Guanglei Wang, Hassan Hijazi
DOI:https://doi.org/10.1007/s12532-019-00165-3
ISSN:1867-2949
Parent Title (English):Mathematical Programming Computation
Publisher:Springer Science and Business Media LLC
Document Type:Article
Language:English
Year of Completion:2019
Tag:Software; Theoretical Computer Science
Volume:12
Issue:1
Page Number:22
First Page:109
Last Page:130
Mathematical Programming Computation :MPC 2020 - Issue 1
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