Max-flow min-cut theorem

On this page
  1. Mathematical statement
  2. Representative formula (exact TeX)
  3. Assumptions
  4. Symbol scope
  5. Intuition, definition, and misconceptions
  6. Adopted derivation guide
  7. Prerequisites
  8. Verification boundary
  9. Next obligation
  10. Same-source structured data

This English edition is an AI candidate and does not yet have an OCME Atlas (GPT-6) Twin closure receipt.

In a finite capacitated network the largest feasible flow value equals the least capacity among all source–sink cuts.

mko-max-flow-min-cut-theorem · theorem · v0.10.0

Mathematical statement

Enumerate each vertex subset S containing the source and excluding the sink. Its capacity sums only directed edges from S to its complement; incoming edges are not counted. Every feasible flow value is at most every cut capacity. Complete cut enumeration determines the minimum cut. If a feasible flow and a cut have equal values, this bound immediately certifies both a maximum flow and a minimum cut. An arbitrary feasible flow or single cut is not automatically optimal. This slice does not claim integral flow, an augmenting-path algorithm proof or a general theorem proof from finitely many instances.

Representative formula (exact TeX)

F(N)=C(N)

Assumptions

  • Use a complete finite directed network with nonnegative exact rational capacities and feasible flows.
  • The vertex bound permits complete enumeration of all source–sink cuts.

Symbol scope

  • F — maximum flow value
  • N — finite flow network
  • C — minimum cut capacity

Intuition, definition, and misconceptions

Enumerate the complete family of legal source–sink cuts.

Check flow≤cut using capacity and conservation for every cut.

An equal-valued feasible pair supplies both optimality certificates.

Do not add incoming-edge capacity to a cut or infer optimality from an arbitrary feasible flow or cut.

Adopted derivation guide

All four cuts and an equal-value two-sided certificate

The original MKO is retained. The guide has its own append-only revision and verification boundaries, not a new Lean proof.

Prerequisites

Verification boundary

Finite enumeration certifies only the specified network, not integrality or the correctness of a particular algorithm.

not_formalized

This does not mean the content is false; it means no replayable computational or formal evidence is registered yet.

Next obligation

Add augmenting paths and Ford–Fulkerson boundaries.

Same-source structured data

This page and the interactive view use the same object and existing language edition; this adds no proof or human review.

Canonical MKO JSON · Plain Markdown