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Now , and both constraints are active. Therefore
The first stationarity equation gives
and the second gives
Thus all multiplier and complementary-slackness conditions hold, and
with minimum value
The observation is that lowering activates the second constraint and moves the optimum to the intersection of the two active boundaries. Rewriting as shows that the feasible set is convex, while is convex. Hence the active-set transition in capped resource allocation and the KKT candidates above give the unique global minima, not merely local stationary points.
Solved by gpt-5.6-sol high.

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