edu.uci.ics.jung.algorithms.flows

Class EdmondsKarpMaxFlow<V,E>

java.lang.Object

edu.uci.ics.jung.algorithms.util.IterativeProcess

edu.uci.ics.jung.algorithms.flows.EdmondsKarpMaxFlow<V,E>

All Implemented Interfaces:

IterativeContext

public class EdmondsKarpMaxFlow<V,E>
extends IterativeProcess

Implements the Edmonds-Karp maximum flow algorithm for solving the maximum flow problem. After the algorithm is executed, the input Map is populated with a Number for each edge that indicates the flow along that edge.

An example of using this algorithm is as follows:

 EdmondsKarpMaxFlow ek = new EdmondsKarpMaxFlow(graph, source, sink, edge_capacities, edge_flows, 
 edge_factory);
 ek.evaluate(); // This instructs the class to compute the max flow
 

See Also:

"Introduction to Algorithms by Cormen, Leiserson, Rivest, and Stein.", "Network Flows by Ahuja, Magnanti, and Orlin.", "Theoretical improvements in algorithmic efficiency for network flow problems by Edmonds and Karp, 1972."

Constructor Summary

Constructors

Constructor and Description
EdmondsKarpMaxFlow(DirectedGraph<V,E> directedGraph, V source, V sink, com.google.common.base.Function<E,java.lang.Number> edgeCapacityTransformer, java.util.Map<E,java.lang.Number> edgeFlowMap, com.google.common.base.Supplier<E> edgeFactory) Constructs a new instance of the algorithm solver for a given graph, source, and sink.

Method Summary

Modifier and Type	Method and Description
DirectedGraph<V,E>	getFlowGraph()
int	getMaxFlow()
java.util.Set<E>	getMinCutEdges()
java.util.Set<V>	getNodesInSinkPartition()
java.util.Set<V>	getNodesInSourcePartition()
void	step() Evaluate the result of the current iteration.

Methods inherited from class edu.uci.ics.jung.algorithms.util.IterativeProcess

done, evaluate, getDesiredPrecision, getIterations, getMaximumIterations, getPrecision, hasConverged, relativePrecision, reset, setDesiredPrecision, setMaximumIterations, setPrecision

Methods inherited from class java.lang.Object

equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Detail

EdmondsKarpMaxFlow

public EdmondsKarpMaxFlow(DirectedGraph<V,E> directedGraph,
                          V source,
                          V sink,
                          com.google.common.base.Function<E,java.lang.Number> edgeCapacityTransformer,
                          java.util.Map<E,java.lang.Number> edgeFlowMap,
                          com.google.common.base.Supplier<E> edgeFactory)

Constructs a new instance of the algorithm solver for a given graph, source, and sink. Source and sink vertices must be elements of the specified graph, and must be distinct.

Parameters:

directedGraph - the flow graph

source - the source vertex

sink - the sink vertex

edgeCapacityTransformer - the Function that gets the capacity for each edge.

edgeFlowMap - the map where the solver will place the value of the flow for each edge

edgeFactory - used to create new edge instances for backEdges

Method Detail

step

public void step()

Description copied from class: IterativeProcess

Evaluate the result of the current iteration.

Specified by:

step in interface IterativeContext

Specified by:

step in class IterativeProcess

getMaxFlow

public int getMaxFlow()

Returns:

the value of the maximum flow from the source to the sink.

getNodesInSinkPartition

public java.util.Set<V> getNodesInSinkPartition()

Returns:

the nodes which share the same partition (as defined by the min-cut edges) as the sink node.

getNodesInSourcePartition

public java.util.Set<V> getNodesInSourcePartition()

Returns:

the nodes which share the same partition (as defined by the min-cut edges) as the source node.

getMinCutEdges

public java.util.Set<E> getMinCutEdges()

Returns:

the edges in the minimum cut.

getFlowGraph

public DirectedGraph<V,E> getFlowGraph()

Returns:

the graph for which the maximum flow is calculated.