Improving the linear relaxation of maximum k-cut with semidefinite-based constraints-Reference-Cited by-同舟云学术

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Improving the linear relaxation of maximum k-cut with semidefinite-based constraints

Published:2019-06 Issue:2 Volume:7 Page:123-151
ISSN:2192-4406
Container-title:EURO Journal on Computational Optimization
language:en
Short-container-title:EURO Journal on Computational Optimization

Author:

Rodrigues de Sousa VilmarJefté,Anjos MiguelF.^ORCID,Le Digabel Sébastien^ORCID

Funder

Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada

Publisher

Elsevier BV

Subject

Computational Mathematics,Control and Optimization,Management Science and Operations Research,Modeling and Simulation

Link

http://link.springer.com/content/pdf/10.1007/s13675-019-00110-y.pdf

Reference50 articles.

1. An extended edge-representative formulation for the k-partitioning problem;Ales;Electron Notes Discrete Math,2016

2. Anjos MF, Ghaddar B, Hupp L, Liers F, Wiegele A (2013) Solving k-way graph partitioning problems to optimality: the impact of semidefinite relaxations and the bundle method. In: Jünger Michael, Reinelt Gerhard (eds) Facets of combinatorial optimization. Springer, Berlin, pp 355–386. 10.1007/978-3-642-38189-8_15

3. Stronger linear programming relaxations of max-cut;Avis;Math Program,2003

4. An application of combinatorial optimization to statistical physics and circuit layout design;Barahona;Oper Res,1988

5. The partition problem;Chopra;Math Program,1993

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