Finite flow network

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.

A nonnegative flow in a finite directed network must respect every edge capacity and conserve flow at each vertex other than source and sink.

mko-finite-flow-network · definition · v0.10.0

Mathematical statement

Use a finite loop-free simple directed graph with distinct source s and sink t. Antiparallel edges are allowed, but each ordered pair appears at most once. Valid capacities/flows are exact nonnegative rationals. Feasibility requires0≤f(e)≤c(e) and complete inflow=outflow at every internal vertex. Cross-check source net outflow against sink net inflow. Zero capacities and disconnected vertices are legal. Feasibility is not maximum flow; no min-cut equality or augmenting-path optimality is claimed ahead of its theorem.

Representative formula (exact TeX)

V(f,s,t)=z

Assumptions

  • Vertices, edges, capacity and flow keys correspond completely one-to-one; no loops or duplicate directed edges.
  • Every sum uses exact rational arithmetic.

Symbol scope

  • V — flow-value operator
  • f — finite edge flow
  • s — source vertex
  • t — sink vertex
  • z — exact flow value

Intuition, definition, and misconceptions

Network qualification fixes the directed-edge convention first.

Capacity and conservation are separate feasibility obligations.

Source and sink flow-value calculations must agree.

A total flow value alone does not check each edge or internal vertex, and a feasible flow is not automatically maximum.

Adopted derivation guide

Checking every edge and internal vertex of a feasible flow

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

Prerequisites

Verification boundary

This slice does not build max-flow/min-cut, residual networks or an optimality proof.

not_formalized

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

Next obligation

Add the max-flow min-cut theorem.

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