Theorem 4.1, proof (p. 95) — Kuhn–Tucker multipliers of the subproblem exist under Slater's condition
OpenShorNonsmooth.Decomposition.exists_kuhnTucker_multiplierconvex-analysisdecompositionkuhn-tuckerp2o-batch-b23ap2o-gran-per-chapterp2o-plan-bookp2o-v1slater-condition
Let and , , be jointly convex, fix , and suppose the constraints satisfy the Slater condition: some has for all . If is an optimal solution of the subproblem , then there exist multipliers with , for all , and
so that .
This is the Kuhn–Tucker theorem applied to the subproblem (4.3)–(4.4); the multipliers it yields are the of formula (4.6).
Preamble
import Mathlib import Definitions.Def_ShorNonsmooth_Decomposition_ValueFunction
Formal statement
namespace ShorNonsmooth.Decomposition
/-- Shor (1985), proof of Theorem 4.1, p. 95 ("By the Kuhn-Tucker theorem …"): for a fixed `xbar`,
if the constraints (4.4) satisfy the Slater condition and `ybar` is an optimal value of `y` in problem
(4.3)–(4.4), then Kuhn–Tucker multipliers `U ≥ 0` exist: complementary slackness holds at `ybar` and
`ybar` minimizes `L_U(xbar, ·)` over all `y`, i.e. `Φ(xbar) = min_y [f₀(xbar, y) + Σ U_i f_i(xbar, y)]`. -/
theorem exists_kuhnTucker_multiplier {l m n : ℕ}
(f₀ : EuclideanSpace ℝ (Fin l) → EuclideanSpace ℝ (Fin m) → ℝ)
(f : Fin n → EuclideanSpace ℝ (Fin l) → EuclideanSpace ℝ (Fin m) → ℝ)
(hf₀ : JointlyConvex f₀) (hf : ∀ i, JointlyConvex (f i))
(xbar : EuclideanSpace ℝ (Fin l)) (hslater : SlaterAt f xbar)
(ybar : EuclideanSpace ℝ (Fin m)) (hybar : IsOptimalY f₀ f xbar ybar) :
∃ U : Fin n → ℝ, IsKuhnTuckerMultiplier f₀ f xbar ybar U := by sorry
end ShorNonsmooth.Decomposition
Source
Shor, Minimization Methods for Non-Differentiable Functions, Springer 1985, p. 95, proof of Theorem 4.1, first display
Human review
Confirmed by the mission captain (proposal self-audit).
Confirmed by the moderator at approval.