Linked from

The 21 pages that link to Maximum flow problem, each with the reason it gives.

• Graph theoryRelated: It uses directed graphs to model capacity-limited movement through a network.

• Bipartite graphRelated: Flow networks reduce bipartite matching to a standard network optimization problem.

• Edge (graph theory)Related: Edge capacities limit how much flow each connection can carry.

• Bipartite matchingRelated: A unit-capacity network converts matching into a flow problem.

• Weighted graphRelated: Edge values can represent capacities rather than costs, changing the optimization task.

• Flow conservationRelated: Conservation ensures flow cannot appear or disappear at intermediate vertices.

• Flow networkRelated: It asks for the network’s maximum possible source-to-sink throughput.

• Circulation problemRelated: A circulation with bounds can be tested by transforming it into a maximum-flow instance.

• Richard M. KarpRelated: Karp developed influential algorithms for network flow and related combinatorial optimization.