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  2. Maximum flow problem - Wikipedia

    en.wikipedia.org/wiki/Maximum_flow_problem

    The maximum flow problem was first formulated in 1954 by T. E. Harris and F. S. Ross as a simplified model of Soviet railway traffic flow. [1] [2] [3]In 1955, Lester R. Ford, Jr. and Delbert R. Fulkerson created the first known algorithm, the Ford–Fulkerson algorithm.

  3. Ford–Fulkerson algorithm - Wikipedia

    en.wikipedia.org/wiki/Ford–Fulkerson_algorithm

    The Ford–Fulkerson method or Ford–Fulkerson algorithm (FFA) is a greedy algorithm that computes the maximum flow in a flow network.It is sometimes called a "method" instead of an "algorithm" as the approach to finding augmenting paths in a residual graph is not fully specified [1] or it is specified in several implementations with different running times. [2]

  4. Push–relabel maximum flow algorithm - Wikipedia

    en.wikipedia.org/wiki/Push–relabel_maximum_flow...

    The push–relabel algorithm is considered one of the most efficient maximum flow algorithms. The generic algorithm has a strongly polynomial O(V 2 E) time complexity, which is asymptotically more efficient than the O(VE 2) Edmonds–Karp algorithm. [2] Specific variants of the algorithms achieve even lower time complexities.

  5. Max-flow min-cut theorem - Wikipedia

    en.wikipedia.org/wiki/Max-flow_min-cut_theorem

    Also, the flow was obtained by Ford-Fulkerson algorithm, so it is the max-flow of the network as well. Also, since any flow in the network is always less than or equal to capacity of every cut possible in a network, the above described cut is also the min-cut which obtains the max-flow.

  6. Flow network - Wikipedia

    en.wikipedia.org/wiki/Flow_network

    Maximum flow problems can be solved in polynomial time with various algorithms (see table). The max-flow min-cut theorem states that finding a maximal network flow is equivalent to finding a cut of minimum capacity that separates the source and the sink, where a cut is the division of vertices such that the source is in one division and the ...

  7. Minimum-cost flow problem - Wikipedia

    en.wikipedia.org/wiki/Minimum-cost_flow_problem

    The minimum cost flow problem can be solved by linear programming, since we optimize a linear function, and all constraints are linear. Apart from that, many combinatorial algorithms exist. [1] Some of them are generalizations of maximum flow algorithms, others use entirely different approaches.

  8. Dinic's algorithm - Wikipedia

    en.wikipedia.org/wiki/Dinic's_algorithm

    Dinic's algorithm or Dinitz's algorithm is a strongly polynomial algorithm for computing the maximum flow in a flow network, conceived in 1970 by Israeli (formerly Soviet) computer scientist Yefim Dinitz. [1]

  9. Edmonds–Karp algorithm - Wikipedia

    en.wikipedia.org/wiki/Edmonds–Karp_algorithm

    In computer science, the Edmonds–Karp algorithm is an implementation of the Ford–Fulkerson method for computing the maximum flow in a flow network in (| | | |) time. The algorithm was first published by Yefim Dinitz in 1970, [1] [2] and independently published by Jack Edmonds and Richard Karp in 1972. [3]