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Theorem 4.18 -- Edmonds's intersection theorem

Proved
DiscreteConvex.MConvexSets.edmonds_intersection_theorem

by Shuze Chen · 1 vote · Sep 27, 2026 · Mathlib 0df444a (Lean v4.33.1)

combinatoricsdiscrete-convex-analysisdiscrete-geometrylinear-optimization

Theorem 4.18 (Edmonds, p.112). For submodular set functions ρ1,ρ2∈S[R]\rho_1, \rho_2 \in S[\mathbb R]ρ1​,ρ2​∈S[R],

max⁡{x(V):x∈P(ρ1)∩P(ρ2)}=min⁡{ρ1(X)+ρ2(V∖X):X⊆V},\max\{x(V) : x \in P(\rho_1) \cap P(\rho_2)\} = \min\{\rho_1(X) + \rho_2(V\setminus X) : X \subseteq V\},max{x(V):x∈P(ρ1​)∩P(ρ2​)}=min{ρ1​(X)+ρ2​(V∖X):X⊆V},

both sides attained. Moreover, if ρ1,ρ2\rho_1, \rho_2ρ1​,ρ2​ are integer valued, P(ρ1)∩P(ρ2)P(\rho_1) \cap P(\rho_2)P(ρ1​)∩P(ρ2​) is an integral polyhedron and the maximum is attained at an integer point. The real max-min equality alone is ordinary LP duality with no discrete content; the integrality clause is the chapter's own combinatorial contribution and is never dropped from the goal even though a milestone-level treatment could prove the real case first.

Formalization Note. Both sides of the max-min equality, and the objective/RHS values, are compared in EReal (via the embedding ToEReal) so that +∞ values of ρ1,ρ2\rho_1,\rho_2ρ1​,ρ2​ are handled uniformly; IsGreatest/IsLeast state that each extremum is genuinely attained, not merely a supremum/infimum.

(Murota, Discrete Convex Analysis, SIAM 2003, DOI 10.1137/1.9780898718508, p.112, Theorem 4.18.)

Preamble
import Mathlib
import Definitions.Def_DiscreteConvex_MConvexSets_SubmodularSetFunction
import Definitions.Def_DiscreteConvex_MConvexSets_SubmodularPolyhedron
import Definitions.Def_DiscreteConvex_MConvexSets_IsIntegerValued
import Definitions.Def_DiscreteConvex_MConvexSets_IsIntegralPolyhedron
import Definitions.Def_DiscreteConvex_MConvexSets_ToEReal
Formal statement
namespace DiscreteConvex.MConvexSets

/-- Theorem 4.18 (Edmonds's intersection theorem; Murota, *Discrete Convex Analysis*, SIAM
2003, p.112). For submodular set functions `ρ1, ρ2 ∈ S[R]`,
`max\{x(V) : x ∈ P(ρ1) ∩ P(ρ2)\} = min\{ρ1(X) + ρ2(V∖X) : X ⊆ V\}`, both sides attained.
Moreover, if `ρ1, ρ2` are integer valued, `P(ρ1) ∩ P(ρ2)` is an integral polyhedron and the
maximum is attained at an integer point. -/
theorem edmonds_intersection_theorem {V : Type*} [Fintype V] [DecidableEq V]
    (ρ1 ρ2 : Finset V → WithTop ℝ) (hρ1 : SubmodularSetFunction ρ1)
    (hρ2 : SubmodularSetFunction ρ2) :
    (∃ m : EReal,
        IsGreatest ((fun x : V → ℝ => ToEReal ((∑ v, x v : ℝ) : WithTop ℝ)) ''
          (SubmodularPolyhedron ρ1 ∩ SubmodularPolyhedron ρ2)) m ∧
        IsLeast ((fun X : Finset V => ToEReal (ρ1 X) + ToEReal (ρ2 Xᶜ)) ''
          (Set.univ : Set (Finset V))) m) ∧
    (IsIntegerValued ρ1 → IsIntegerValued ρ2 →
      IsIntegralPolyhedron (SubmodularPolyhedron ρ1 ∩ SubmodularPolyhedron ρ2) ∧
      ∃ x ∈ SubmodularPolyhedron ρ1 ∩ SubmodularPolyhedron ρ2, (∀ v, ∃ k : ℤ, x v = (k : ℝ)) ∧
        IsGreatest ((fun y : V → ℝ => ToEReal ((∑ v, y v : ℝ) : WithTop ℝ)) ''
          (SubmodularPolyhedron ρ1 ∩ SubmodularPolyhedron ρ2))
          (ToEReal ((∑ v, x v : ℝ) : WithTop ℝ))) := by sorry

end DiscreteConvex.MConvexSets
Source
Murota, Discrete Convex Analysis, SIAM 2003, DOI 10.1137/1.9780898718508, p.112, Theorem 4.18
Human review
  • Endorsed by Community (Bot) · Oct 1, 2026

    Confirmed by the moderator at approval.

  • Endorsed by Shuze Chen · Oct 1, 2026

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

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