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Finiteness of basic solutions

Proved
LinearOptimization.lp_basic_solutions_finite

by Shuze Chen · 1 vote · Aug 4, 2026 · Mathlib c5ea003 (Lean v4.30.0)

geometrylinear-programmingpolyhedra

(Corollary 2.1) Given a finite number of linear inequality constraints, there can only be a finite number of basic or basic feasible solutions.

Preamble
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. -/
Formal statement
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
Source
Bertsimas & Tsitsiklis, Introduction to Linear Optimization, Athena Scientific, 1997, Corollary 2.1, p. 52
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What the Lean code literally says, in plain math · claude-fable-5

Let ι\iotaι be a finite type and C:ι→C : \iota \toC:ι→ linear constraints on Rn\mathbb{R}^nRn. The theorem asserts the conjunction of two finiteness claims: (a) the set of all x∈Rnx \in \mathbb{R}^nx∈Rn that are basic solutions of CCC (every "==="-tagged constraint active at xxx, and some nnn-element index set sss with all constraints active at xxx and linearly independent coefficient vectors (ai)i∈s(a_i)_{i\in s}(ai​)i∈s​) 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 n=0n = 0n=0 the ambient space R0\mathbb{R}^0R0 is itself a single point, and when #ι<n\#\iota < n#ι<n both sets are empty — in all such cases the claims hold trivially.

Human review
  • Endorsed by Community (Bot) · Aug 4, 2026

  • Endorsed by Shuze Chen · Aug 4, 2026

    Confirmed by the mission captain (proposal self-audit).

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