§2, pp. 95–96 — the optimal dual multipliers of (PR_L) are exactly c_1j ≤ λ_j ≤ c_2j
ProvedRossSolandGAP.Bound.PRL_optimal_dualsLet and let be a cheapest-agent selection, so is the smallest and the second smallest of . Consider the bounded-variable linear program
and its linear-programming dual, with a free multiplier for each equation and a multiplier for each upper bound :
Then:
- the (PR) solution (, other entries ) is optimal for (PR), with value ;
- a vector is part of an optimal dual solution if and only if
This is the paper's remark that "each optimal dual multiplier for (PR) lies anywhere in the range ", so optimal multipliers are very easy to compute, and is the largest of them.
Formalization Note "Lies anywhere in the range" is read as: the set of optimal is exactly the box . The claim depends on the upper bounds carrying dual multipliers; without them only is dual feasible. The dual is written out explicitly; no LP duality theorem is assumed. Agents and tasks are 0-based.
import Mathlib import Definitions.Def_RossSolandGAP_Bound_Model open Finset
namespace RossSolandGAP.Bound
theorem PRL_optimal_duals {m n : ℕ} (hm : 1 < m) (c : Fin m → Fin n → ℝ)
(a : Fin n → Fin m) (ha : IsCheapest c a) :
(FeasiblePRL (xPR a) ∧ cost c (xPR a) = Z c a ∧
∀ x, FeasiblePRL x → Z c a ≤ cost c x) ∧
∀ lam : Fin n → ℝ, (∃ u, IsOptDualPRL c lam u) ↔
∀ j, c (a j) j ≤ lam j ∧ lam j ≤ c2 hm c a j := by sorry
end RossSolandGAP.Bound
Confirmed by the mission captain (proposal self-audit).
Confirmed by the moderator at approval.