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Ford Fulkerson Maximum Flow Algorithm

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Problem Definition: Maximum flow finds feasible flow through single-source, single-sink network
Network consists of source s and sink t with equal flow except for s and t
Key Terminology: Augmenting paths include non-full forward and non-empty backward edges
Minimal cut capacity is maximum flow through augmented path
Residual capacity is original capacity minus flow through edge
Residual graph shows additional possible flow paths
Algorithm Steps: Initialize all edge flows to 0
Add augmenting paths while there's one between source and sink
Update residual graph
Return maximum flow
Applications: Bipartite matching for job assignments
Airline scheduling
Data mining
Network reliability
Image segmentation
Distributed computing