Abstract
We consider several semidefinite programming relaxations for the max-k-cut problem, with increasing complexity. The optimal solution of the weakest presented semidefinite programming relaxation has a closed form expression that includes the largest Laplacian eigenvalue of the graph under consideration. This is the first known eigenvalue bound for the max-k-cut when k>2 that is applicable to any graph. This bound is exploited to derive a new eigenvalue bound on the chromatic number of a graph. For regular graphs, the new bound on the chromatic number is the same as the well-known Hoffman bound; however, the two bounds are incomparable in general. We prove that the eigenvalue bound for the max-k-cut is tight for several classes of graphs. We investigate the presented bounds for specific classes of graphs, such as walk-regular graphs, strongly regular graphs, and graphs from the Hamming
association scheme.
Original language | English |
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Pages (from-to) | 216 - 234 |
Number of pages | 18 |
Journal | Linear Algebra and its Applications |
Volume | 488 |
DOIs | |
Publication status | Published - 1 Jan 2016 |
Keywords
- max-k-cut
- chromatic number
- semidefinite programming
- Laplacian eigenvalues
- walk-regular graphs
- association schemes
- strongly regular graphs
- Hamming graphs