David Nickerson reports odd behaviour involving a drag start point
[sgt-puzzles/ydirson.git] / maxflow.h
blobd490f45421155796d43dfd36d3936c15565be6db
1 /*
2 * Edmonds-Karp algorithm for finding a maximum flow and minimum
3 * cut in a network. Almost identical to the Ford-Fulkerson
4 * algorithm, but apparently using breadth-first search to find the
5 * _shortest_ augmenting path is a good way to guarantee
6 * termination and ensure the time complexity is not dependent on
7 * the actual value of the maximum flow. I don't understand why
8 * that should be, but it's claimed on the Internet that it's been
9 * proved, and that's good enough for me. I prefer BFS to DFS
10 * anyway :-)
13 #ifndef MAXFLOW_MAXFLOW_H
14 #define MAXFLOW_MAXFLOW_H
17 * The actual algorithm.
19 * Inputs:
21 * - `scratch' is previously allocated scratch space of a size
22 * previously determined by calling `maxflow_scratch_size'.
24 * - `nv' is the number of vertices. Vertices are assumed to be
25 * numbered from 0 to nv-1.
27 * - `source' and `sink' are the distinguished source and sink
28 * vertices.
30 * - `ne' is the number of edges in the graph.
32 * - `edges' is an array of 2*ne integers, giving a (source, dest)
33 * pair for each network edge. Edge pairs are expected to be
34 * sorted in lexicographic order.
36 * - `backedges' is an array of `ne' integers, each a distinct
37 * index into `edges'. The edges in `edges', if permuted as
38 * specified by this array, should end up sorted in the _other_
39 * lexicographic order, i.e. dest taking priority over source.
41 * - `capacity' is an array of `ne' integers, giving a maximum
42 * flow capacity for each edge. A negative value is taken to
43 * indicate unlimited capacity on that edge, but note that there
44 * may not be any unlimited-capacity _path_ from source to sink
45 * or an assertion will be failed.
47 * Output:
49 * - `flow' must be non-NULL. It is an array of `ne' integers,
50 * each giving the final flow along each edge.
52 * - `cut' may be NULL. If non-NULL, it is an array of `nv'
53 * integers, which will be set to zero or one on output, in such
54 * a way that:
55 * + the set of zero vertices includes the source
56 * + the set of one vertices includes the sink
57 * + the maximum flow capacity between the zero and one vertex
58 * sets is achieved (i.e. all edges from a zero vertex to a
59 * one vertex are at full capacity, while all edges from a
60 * one vertex to a zero vertex have no flow at all).
62 * - the returned value from the function is the total flow
63 * achieved.
65 int maxflow_with_scratch(void *scratch, int nv, int source, int sink,
66 int ne, const int *edges, const int *backedges,
67 const int *capacity, int *flow, int *cut);
70 * The above function expects its `scratch' and `backedges'
71 * parameters to have already been set up. This allows you to set
72 * them up once and use them in multiple invocates of the
73 * algorithm. Now I provide functions to actually do the setting
74 * up.
76 int maxflow_scratch_size(int nv);
77 void maxflow_setup_backedges(int ne, const int *edges, int *backedges);
80 * Simplified version of the above function. All parameters are the
81 * same, except that `scratch' and `backedges' are constructed
82 * internally. This is the simplest way to call the algorithm as a
83 * one-off; however, if you need to call it multiple times on the
84 * same network, it is probably better to call the above version
85 * directly so that you only construct `scratch' and `backedges'
86 * once.
88 * Additional return value is now -1, meaning that scratch space
89 * could not be allocated.
91 int maxflow(int nv, int source, int sink,
92 int ne, const int *edges, const int *capacity,
93 int *flow, int *cut);
95 #endif /* MAXFLOW_MAXFLOW_H */