// Returns a negative cycle on the graph, if it exists.
// Judicious choice of this cycle is the main way to get asymptotic speed-up.
// Current implementation: Application of Bellman-Ford shortest path algorithm.
public static Tuple <List <Edge>, long> FindNegativeCycle(CirculationGraph graph)
{
// First reset the metadata associated with this algorithm.
foreach (Node n in graph.Nodes)
{
n.MetaData = new NodeMetaData();
}
// Decide which edges should even be considered for increasing flow by those with positive Free space.
List <Edge> viableEdges = new List <Edge>();
foreach (Edge e in graph.Edges)
{
if (e.Free > 0)
{
viableEdges.Add(e);
}
}
// Iterate Bellman-Ford n-1 times.
for (int i = 0; i < graph.Nodes.Count - 1; i++)
{
foreach (Edge e in viableEdges)
{
if (e.Target.MetaData.Distance > e.Source.MetaData.Distance + e.Cost)
{
e.Target.MetaData.Distance = e.Source.MetaData.Distance + e.Cost;
e.Target.MetaData.PredEdge = e;
}
}
}
// Iterate over all edges one last time to find negative cycles.
foreach (Edge e in viableEdges)
{
if (e.Target.MetaData.Distance > e.Source.MetaData.Distance + e.Cost)
{
return(FindBellmanFordCycle(e.Source));
}
}
// Return a null cycle if no negative cycles are found; signals that there are no more negative cycles.
return(Tuple.Create <List <Edge>, long>(null, 0));
}
// Changes graph state into a minimum-cost circulation, if it exists.
public static void FindMinCostCirculation(CirculationGraph graph, int smoothingIterations = -1)
{
int numIterations = 0;
// Represent a cycle as a tuple of the edges on the cycle and the minimum free capacity.
Tuple <List <Edge>, long> cycle = FindNegativeCycle(graph);
while (cycle.Item1 != null && numIterations != smoothingIterations)
{
// Force flow equal to the minimum free capacity through all the edges on the negative cycle.
foreach (Edge e in cycle.Item1)
{
e.AddFlow(cycle.Item2);
}
// Ensure that our new flow does not violate any flow conditions.
graph.CheckConsistentCirculation();
cycle = FindNegativeCycle(graph);
numIterations++;
}
}
