  The paper concerns multiobjective linear optimization problems in R^n that
are parameterized with respect to the right-hand side perturbations of
inequality constraints. Our focus is on measuring the variation of the feasible
set and the Pareto front mappings around a nominal element while paying
attention to some specific directions. This idea is formalized by means of the
so-called epigraphical multifunction, which is defined by adding a fixed cone
to the images of the original mapping. Through the epigraphical feasible and
Pareto front mappings we describe the corresponding vector subdifferentials,
and employ them to verifying Lipschitzian stability of the perturbed mappings
with computing the associated Lipschitz moduli. The particular case of ordinary
linear programs is analyzed, where we show that the subdifferentials of both
multifunctions are proportional subsets. We also provide a method for computing
the optimal value of linear programs without knowing any optimal solution. Some
illustrative examples are also given in the paper.
