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Compressed polytopes and statistical disclosure limitation. (English) Zbl 1121.52028
A lattice polytope $$P$$ is said to be compressed if every pulling triangulation of it (using only lattice points from $$P$$) is unimodular. (An example is the Birkhoff polytope of doubly stochastic matrices.) The author characterizes the compressed polytopes by their facet defining inequalities, shows that every compressed is affinely isomorphic to a 0/1-polytope and proves a result about pulling triangulations for highly symmetric polytopes. Also the compressed cut polytopes are characterized, and the connection between compressed polytopes and linear optimization is investigated. The last part of the paper refers to applications of these results in statistical disclosure limitation providing new families of marginals where linear programming yields sharp upper bounds on cell entries. These results also refer to integer programming.

##### MSC:
 52B20 Lattice polytopes in convex geometry (including relations with commutative algebra and algebraic geometry) 90C10 Integer programming 62H17 Contingency tables 52C07 Lattices and convex bodies in $$n$$ dimensions (aspects of discrete geometry)
polymake
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