Finiteness of basic solutions
ProvedLinearOptimization.lp_basic_solutions_finite(Corollary 2.1) Given a finite number of linear inequality constraints, there can only be a finite number of basic or basic feasible solutions.
import Mathlib.Data.Set.Finite.Basic import Definitions.Def_BasicSolution /-- **B&T Corollary 2.1 (p. 52).** A finite family of linear constraints admits only finitely many basic solutions, and hence only finitely many basic feasible solutions. -/
theorem LinearOptimization.lp_basic_solutions_finite {ι : Type} [Fintype ι] {n : ℕ}
(C : ι → LinearConstraint n) :
{x | IsBasicSolution C x}.Finite ∧
{x | IsBasicFeasibleSolution C x}.Finite := by
sorry
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What the Lean code literally says, in plain math · claude-fable-5
Let be a finite type and linear constraints on . The theorem asserts the conjunction of two finiteness claims: (a) the set of all that are basic solutions of (every ""-tagged constraint active at , and some -element index set with all constraints active at and linearly independent coefficient vectors ) is a finite set; and (b) the set of all basic feasible solutions (basic solutions that moreover satisfy every constraint) is a finite set. No nonemptiness or feasibility hypotheses are made; when the ambient space is itself a single point, and when both sets are empty — in all such cases the claims hold trivially.
Confirmed by the mission captain (proposal self-audit).