Theorem 3.1, p. 7 — customization gains at most a factor m, and the order is tight
ProvedCustAssort.Value.theorem_3_1Let products have positive revenues, nonnegative type-dependent MNL preference weights, and a no-purchase weight of one. Let the customer types arrive with nonnegative probabilities summing to one. For a first-stage assortment of size at most , permits a separate subset for each type, while offers the same assortment to every type. Then
The order is tight: for every , the paper's family with , , , , , and when (zero otherwise), satisfies the model assumptions and has and
This compares the best expected revenue with and without customer-type customization. The explicit family realizes the paper's assertion with a positive MMNL benchmark.
Formalization Note Products and types are 0-based Fin indices. The explicit constant is pinned from the proof's bounds and . No revenue-order hypothesis is imposed: the instance has increasing revenues.
import Mathlib import Definitions.Def_CustAssort_Value_Setting
namespace CustAssort.Value
/-- Theorem 3.1, page 7, including the explicit tightness family of pages 8–9. -/
theorem theorem_3_1 :
(∀ (n m K : ℕ) (r : Fin n → ℝ) (v : Fin n → Fin m → ℝ)
(θ : Fin m → ℝ),
(∀ i, 0 < r i) → (∀ i j, 0 ≤ v i j) → (∀ j, 0 ≤ θ j) →
(∑ j : Fin m, θ j) = 1 →
zMMNL θ v r K ≤ zCAP θ v r K ∧
zCAP θ v r K ≤ (m : ℝ) * zMMNL θ v r K) ∧
(∀ m : ℕ, 2 ≤ m →
(∀ i : Fin m, 0 < revI (aStar m) m i) ∧
(∀ i j : Fin m, 0 ≤ vI (bStar m) m i j) ∧
(∀ j : Fin m, 0 ≤ thetaI (aStar m) m j) ∧
(∑ j : Fin m, thetaI (aStar m) m j) = 1 ∧
0 < zMMNL (thetaI (aStar m) m) (vI (bStar m) m)
(revI (aStar m) m) m ∧
(m : ℝ) / 6 * zMMNL (thetaI (aStar m) m) (vI (bStar m) m)
(revI (aStar m) m) m ≤
zCAP (thetaI (aStar m) m) (vI (bStar m) m)
(revI (aStar m) m) m) := by sorry
end CustAssort.Value
Confirmed by the mission captain (proposal self-audit).
Confirmed by the moderator at approval.