  Our main goal is to compute or estimate the calmness modulus of the argmin
mapping of linear semi-infinite optimization problems under canonical
perturbations, i.e., perturbations of the objective function together with
continuous perturbations of the right-hand-side of the constraint system (with
respect to an index ranging in a compact Hausdorff space). Specifically, we
provide a lower bound on the calmness modulus for semi-infinite programs with
unique optimal solution which turns out to be the exact modulus when the
problem is finitely constrained. The relationship between the calmness of the
argmin mapping and the same property for the (sub)level set mapping (with
respect to the objective function), for semi-infinite programs and without
requiring the uniqueness of the nominal solution, is explored too, providing an
upper bound on the calmness modulus of the argmin mapping. When confined to
finitely constrained problems, we also provide a computable upper bound as it
only relies on the nominal data and parameters, not involving elements in a
neighborhood. Illustrative examples are provided.
