Integer and combinatorial optimization
Integer and combinatorial optimization
Facets of the clique partitioning polytope
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Mathematical Programming: Series A and B
Facet-defining inequalities for the simple graph partitioning polytope
Discrete Optimization
A mixed integer programming model for the parsimonious loss of heterozygosity problem
ISBRA'12 Proceedings of the 8th international conference on Bioinformatics Research and Applications
An Integer Programming Formulation of the Parsimonious Loss of Heterozygosity Problem
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
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In this paper we prove two lifting theorems for the clique partitioning polytope, which provide sufficient conditions for a valid inequality to be facet-defining. In particular, if a valid inequality defines a facet of the polytope corresponding to the complete graph K"m on m vertices, it defines a facet for the polytope corresponding to K"n for all nm. This answers a question raised by Grotschel and Wakabayashi. Further, for the case of arbitrary graphs, we characterize when the so-called 2-partition inequalities define facets.