The same weak duality certificate gives the upper bound for every feasible point. Keep and solve the tight second and third constraints:These are nonnegative precisely when their numerators are nonnegative. The remaining first-constraint slack is . All three are positive for sufficiently small perturbations, so the point is feasible and attains the bound. This illustrates linear programming sensitivity within a fixed optimal basis:More generally this expression is valid throughout the region specified by those three feasibility inequalities.
With , the conditions reduce toThe endpoints are included. Outside this interval the bound cannot be attained: its equality conditions require exactly the point above, which then has a negative or violates the first constraint. Whenever feasible, the problem attains a maximum because the first constraint and nonnegativity bound all coordinates, so its value is strictly smaller outside the interval. For it is infeasible. Thus the range is exact, not just a sufficient neighborhood.
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