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Chapter 24: Flow Networks

This generated chapter is split into sections because the merged source exceeds the public reference threshold.

Learning objectives

  • Explain the main ideas and vocabulary in Flow Networks.
  • Work through the source examples for Flow Networks without depending on raw chunk order.
  • Use Flow Networks as selective reference when learner modules point back to Introduction To Algorithms Clrs.

Prerequisites

  • Earlier prerequisite concepts leading into Chapter 24: Flow Networks.

Module targets

  • module-02-sorting-searching-structures
  • module-03-graph-algorithms

AI companion modes

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Source-of-truth note

This unit is anchored to Introduction To Algorithms Clrs and the source chapter "Chapter 24: Flow Networks". Use external resources only to clarify, extend, or modernize details without replacing the chapter's conceptual spine.

External enrichment

No chapter-specific enrichment resources are curated yet. Add them in the unit manifest when a source clearly improves learning.

Source provenance

  • Primary source: Introduction To Algorithms Clrs
  • Source chapter 24: Chapter 24: Flow Networks
  • Raw source file: 209-24-1-flow-networks.md
  • Raw source file: 210-24-1-flow-networks.md
  • Raw source file: 211-24-2-the-ford-fulkerson-method.md
  • Raw source file: 212-24-2-the-ford-fulkerson-method.md
  • Raw source file: 213-24-2-the-ford-fulkerson-method.md
  • Raw source file: 214-24-2-the-ford-fulkerson-method.md
  • Raw source file: 215-24-2-the-ford-fulkerson-method.md
  • Raw source file: 216-24-3-maximum-bipartite-matching.md
  • Raw source file: 217-24-3-maximum-bipartite-matching.md
  • Raw source file: 218-24-3-maximum-bipartite-matching.md
  • Raw source file: 219-24-3-maximum-bipartite-matching.md

Sections

  • No section routes are currently published for this chapter.