Linked from

The 14 pages that link to Bipartite matching, each with the reason it gives.

• Bipartite graphBroader topic: It formalizes one-to-one assignments between two kinds of entities.

• Matching (graph theory)Broader topic: Many practical pairing problems have two distinct sides, such as workers and jobs.

• Assignment problemNarrower topic: An assignment is a matching, with costs added to distinguish among possible matchings.

• Augmenting pathRelated: Alternating augmenting paths increase a matching by exchanging matched and unmatched edges.

• Maximum flow problemRelated: A matching can be found by representing assignments as unit-capacity flow paths.

• Flow networkRelated: A flow construction can find the largest compatible assignment.

• Edmonds–Karp algorithmRelated: A unit-capacity flow construction lets Edmonds–Karp find maximum bipartite matchings.

• Max-flow min-cut theoremRelated: A flow network reduces maximum matching to maximum flow, while cuts certify matching-size bounds.

• Circulation problemRelated: Matching constraints can be represented using unit-capacity flow and circulation constructions.

• Dilworth's theoremRelated: A matching construction converts the poset problem into a chain-cover problem.

• Minimum-cost flow problemRelated: Matching can be formulated as a unit-capacity minimum-cost flow problem.

• Kőnig's theoremNarrower topic: The theorem provides a vertex-cover certificate for the optimum of this central problem.

• Dinitz theoremRelated: Matching algorithms provide constructive tools for the theorem’s color assignments.

• Richard M. KarpRelated: Matching is a central combinatorial problem connected to Karp’s algorithmic work.