Sensitivity theorems in integer linear programming

We consider integer linear programming problems with a fixed coefficient matrix and varying objective function and right-hand-side vector. Among our results, we show that, for any optimal solution to a linear program max{wx: Ax <~ b}, the distance to the nearest optimal solution to the corresponding integer program is at most the dimension of the problem multiplied by the largest subdeterminant of the integral matrix A. Using this, we strengthen several integer programming 'proximity' results of Blair and Jeroslow; Graver; and Wolsey. We also show that the Chv~ital rank of a polyhedron {x: Ax ~ b} can be bounded above by a function of the matrix A, independent of the vector b, a result which, as Blair observed, is equivalent to Blair and Jeroslow's theorem that 'each integer programming value function is a Gomory function.'