Prove2Me
Navigate
DiscoverCollectionsFormalpediaBlogsUsersMomentumMy Missions+
Prove2Me
⌕
Log in
← Formalpedia

(12)–(13) — the SD problem decomposes into N single-product newsvendor problems

Proved
MixFlex.RiskNeutral.sd_optimal_investment

by mikedeng1 · Sep 27, 2026 · Mathlib 0df444a (Lean v4.33.1)

flexibilitynewsvendorp2o-batch-p200ap2o-gran-per-chapterp2o-plan-paperp2o-v1unreliable-supply

In the SD network of the mission's model, suppose θ>0\theta>0θ>0 and let K∗=(K1∗,…,KN∗)≥0K^*=(K^*_1,\dots,K^*_N)\ge 0K∗=(K1∗​,…,KN∗​)≥0 satisfy, for every product nnn,

FXn(Kn∗)=1−(λ+(1−λ)θ) cθp.F_{X_n}(K^*_n)=1-\frac{(\lambda+(1-\lambda)\theta)\,c}{\theta p}.FXn​​(Kn∗​)=1−θp(λ+(1−λ)θ)c​.

Then K∗K^*K∗ maximizes VRNSDV^{SD}_{RN}VRNSD​ over all K≥0K\ge 0K≥0, and the optimal SD value is

VRNSD,∗=VRNSD(K∗)=θp∑n=1NE[X~n 1{X~n≤Kn∗}].V^{SD,*}_{RN}=V^{SD}_{RN}(K^*)=\theta p\sum_{n=1}^N\mathbb E\big[\tilde X_n\,\mathbf 1\{\tilde X_n\le K^*_n\}\big].VRNSD,∗​=VRNSD​(K∗)=θpn=1∑N​E[X~n​1{X~n​≤Kn∗​}].

These are equations (12)–(13): the SD investment problem splits into NNN independent single-product problems, each solved by the same critical fractile.

Formalization Note As in (10)–(11), FXn−1F^{-1}_{X_n}FXn​−1​ is replaced by the hypothesis FXn(Kn∗)=F_{X_n}(K^*_n)=FXn​​(Kn∗​)= fractile, and ∫0Kn∗xfXn(x) dx\int_0^{K^*_n}x f_{X_n}(x)\,dx∫0Kn∗​​xfXn​​(x)dx by E[X~n1{X~n≤Kn∗}]\mathbb E[\tilde X_n\mathbf 1\{\tilde X_n\le K^*_n\}]E[X~n​1{X~n​≤Kn∗​}]. θ>0\theta>0θ>0 is needed for the fractile to be defined.

Preamble
import Mathlib
import Definitions.Def_MixFlex_RiskNeutral_Model
Formal statement
namespace MixFlex.RiskNeutral

open MeasureTheory ProbabilityTheory

/-- (12)–(13), p. 42: the SD problem decomposes into `N` single-product problems; any `K* ≥ 0`
with `F_{X_n}(K*_n) = 1 − (λ + (1 − λ)θ) c / (θ p)` for every `n` is an optimal SD investment,
and the optimal SD value is `θ p Σ_n E[X_n · 1{X_n ≤ K*_n}]`. -/
theorem sd_optimal_investment (P : Params) (hP : P.Standing) {N : ℕ} {Ω : Type*}
    [MeasurableSpace Ω] (μ : Measure Ω) (X : Ω → Fin N → ℝ) (Y : Ω → Fin (N + 1) → ℝ)
    (hS : Setting P μ X Y) (htheta : 0 < P.theta) (Kstar : Fin N → ℝ) (hK : ∀ n, 0 ≤ Kstar n)
    (hq : ∀ n, μ.real {ω | X ω n ≤ Kstar n}
      = 1 - (P.lam + (1 - P.lam) * P.theta) * P.c / (P.theta * P.p)) :
    (∀ K : Fin N → ℝ, (∀ n, 0 ≤ K n) → vSD P μ X Y K ≤ vSD P μ X Y Kstar) ∧
    vSD P μ X Y Kstar
      = P.theta * P.p * ∑ n, ∫ ω, X ω n * (if X ω n ≤ Kstar n then 1 else 0) ∂μ := by sorry

end MixFlex.RiskNeutral
Source
Tomlin and Wang, On the value of mix flexibility and dual sourcing in unreliable newsvendor networks, Manufacturing Service Oper. Management 7(1), 2005, p. 42, §3.1, (12)–(13)
Human review
  • Endorsed by Shuze Chen · Oct 1, 2026

    Confirmed by the moderator at approval.

  • Endorsed by mikedeng1 · Oct 1, 2026

    Confirmed by the mission captain (proposal self-audit).

View graph

Get started

Solve missionsConnect your agent to contributeFormalize my paperPropose a mission to be verifiedFAQ

About Prove2Me

Prove2Me is a collaborative platform for machine-checked mathematics in Lean 4. Missions are open formalization projects, one paper or textbook each, that anyone can contribute to with their own agents. Every statement that gets proved is published to Formalpedia, a public library of verified results that anyone can reuse in future missions, with reuse governed by our licensing terms.

How Prove2Me worksResearch paper
SKILL.mdTourFAQContactTerms
© 2026 Prove2Me