A solution is reliable iff it is feasible for (∗)
ProvedRobustLP.Counterpart.reliable_iff_starlinear-programmingp2o-batch-p200bp2o-gran-per-chapterp2o-plan-paperp2o-v1robust-optimization
Let an uncertain linear program with data and uncertain-entry sets be given, and let , . A vector is reliable — feasible for the nominal problem, and for every row and all with () satisfying — if and only if is feasible for
This identifies the worst case of the interval uncertainty and turns the semi-infinite requirement (ii) into finitely many convex constraints.
Formalization Note The hypotheses and are the paper's standing assumptions on the uncertainty level and the tolerance.
Preamble
import Mathlib import Definitions.Def_RobustLP_Counterpart_UncertainLP import Definitions.Def_RobustLP_Counterpart_Reliable import Definitions.Def_RobustLP_Counterpart_RobustCounterparts
Formal statement
namespace RobustLP.Counterpart
/-- **Reliability ⇔ (∗)** (Ben-Tal–Nemirovski 2000, §3.1, p. 417). For `ε > 0` and `δ > 0`,
`x` is reliable (conditions (i) and (ii)) if and only if `x` is a feasible solution of (∗). -/
theorem reliable_iff_star {n p m : ℕ} (L : UncertainLP n p m)
(ε δ : ℝ) (hε : 0 < ε) (hδ : 0 < δ) (x : Fin n → ℝ) :
L.Reliable ε δ x ↔ L.StarFeasible ε δ x := by sorry
end RobustLP.Counterpart
Source
Ben-Tal and Nemirovski, Robust solutions of Linear Programming problems contaminated with uncertain data, Math. Program. Ser. A 88 (2000) 411–424, p. 417, §3.1, 'It is clearly seen that x is reliable if and only if x is a feasible solution of the following optimization problem: … (∗)'
Human review
Confirmed by the mission captain (proposal self-audit).
Confirmed by the moderator at approval.