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A lower bound for the complexity of linear optimization from a quantifier-elimination point of view
We discuss the impact of data structures in quantifier elimination.
We analyze the arithmetic complexity of the feasibility problem in
linear optimization theory as a quantifier-elimination problem. For
the case of polyhedra defined by halfspaces in we prove
that, if dense representation is used to code polynomials, any
quantifier-free formula expressing the set of parameters describing
nonempty polyhedra has size