Use the sign convention
for the Lagrangian function in constrained optimization. The Lagrangian dual problem is
where is the convex conjugate. For this convex problem with affine equality constraints, the stationarity and feasibility parts of the Karush-Kuhn-Tucker conditions are
They say exactly that the displayed operator satisfies
Thus its zeros are precisely the primal-dual optimal points, subject to the usual attainment assumptions.
For and , the Euclidean inner product gives
The last two terms cancel by the defining property of the matrix transpose, and the first is nonnegative by part a. Hence is a monotone operator.

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