Lemma 1, p. 37 — (1/τ)Φ_τ(d, s) = Φ(d/τ, s/τ), and x optimal for Φ(d/τ, s/τ) iff τx optimal for Φ_τ(d, s)
ProvedMarketInterference.FluidLimit.lemma_1linear-programmingnetwork-flowp2o-batch-pfp2ap2o-gran-per-chapterp2o-plan-paperp2o-v1scaling
Let be a demand vector, a supply vector and a density. Then the value of the matching program (2) scales as
and a flow is optimal for if and only if is optimal for .
The identity converts the expected scaled value into , the form in which the fluid limit is taken.
Formalization Note The paper's second sentence ("if and are the respective optimal primal solutions … then ") presupposes unique optima; it is stated here as the equivalence of optimality under , which is the paper's claim when the optima are unique. The density is any positive real.
Preamble
import Mathlib import Definitions.Def_MarketInterference_FluidBias_NetworkLP
Formal statement
namespace MarketInterference.FluidLimit
/-- Lemma 1 (arXiv:2205.02274v4, p. 37, (27)): for integer demand and supply vectors and every
density `τ > 0`, `(1/τ) Φ_τ(d, s) = Φ((1/τ) d, (1/τ) s)`, and `x` is optimal for the right-hand side
iff `τ x` is optimal for the left-hand side. -/
theorem lemma_1 {nd ns : ℕ} {I E : Type} [Fintype E] [DecidableEq I]
(N : MarketInterference.FluidBias.Network nd ns I E) (τ : ℝ) (hτ : 0 < τ) (d : Fin nd → ℕ) (s : Fin ns → ℕ) :
(1 / τ) * MarketInterference.FluidBias.Phi N τ (fun i => (d i : ℝ)) (fun j => (s j : ℝ)) =
MarketInterference.FluidBias.Phi N 1 (fun i => 1 / τ * (d i : ℝ)) (fun j => 1 / τ * (s j : ℝ)) ∧
∀ x : E → ℝ, MarketInterference.FluidBias.IsOptimal N 1 (fun i => 1 / τ * (d i : ℝ)) (fun j => 1 / τ * (s j : ℝ)) x ↔
MarketInterference.FluidBias.IsOptimal N τ (fun i => (d i : ℝ)) (fun j => (s j : ℝ)) (τ • x) := by sorry
end MarketInterference.FluidLimit
Source
Bright, Delarue and Lobel, Reducing Marketplace Interference Bias Via Shadow Prices, arXiv:2205.02274v4, p. 37, Lemma 1, (27)
Human review
Confirmed by the mission captain (proposal self-audit).
Confirmed by the moderator at approval.