* This file is a part of LEMON, a generic C++ optimization library
* Copyright (C) 2003-2008
* Egervary Jeno Kombinatorikus Optimalizalasi Kutatocsoport
* (Egervary Research Group on Combinatorial Optimization, EGRES).
* Permission to use, modify and distribute this software is granted
* provided that this copyright notice appears in all copies. For
* precise terms see the accompanying LICENSE file.
* This software is provided "AS IS" with no warranty of any kind,
* express or implied, and with no claim as to its suitability for any
#ifndef LEMON_CAPACITY_SCALING_H
#define LEMON_CAPACITY_SCALING_H
/// \ingroup min_cost_flow
/// \brief Capacity scaling algorithm for finding a minimum cost flow.
#include <lemon/bin_heap.h>
/// \addtogroup min_cost_flow
/// \brief Implementation of the capacity scaling algorithm for
/// finding a minimum cost flow.
/// \ref CapacityScaling implements the capacity scaling version
/// of the successive shortest path algorithm for finding a minimum
/// \tparam Digraph The digraph type the algorithm runs on.
/// \tparam LowerMap The type of the lower bound map.
/// \tparam CapacityMap The type of the capacity (upper bound) map.
/// \tparam CostMap The type of the cost (length) map.
/// \tparam SupplyMap The type of the supply map.
/// - Arc capacities and costs should be \e non-negative \e integers.
/// - Supply values should be \e signed \e integers.
/// - The value types of the maps should be convertible to each other.
/// - \c CostMap::Value must be signed type.
template < typename Digraph,
typename LowerMap = typename Digraph::template ArcMap<int>,
typename CapacityMap = typename Digraph::template ArcMap<int>,
typename CostMap = typename Digraph::template ArcMap<int>,
typename SupplyMap = typename Digraph::template NodeMap<int> >
TEMPLATE_DIGRAPH_TYPEDEFS(Digraph);
typedef typename CapacityMap::Value Capacity;
typedef typename CostMap::Value Cost;
typedef typename SupplyMap::Value Supply;
typedef typename Digraph::template ArcMap<Capacity> CapacityArcMap;
typedef typename Digraph::template NodeMap<Supply> SupplyNodeMap;
typedef typename Digraph::template NodeMap<Arc> PredMap;
/// The type of the flow map.
typedef typename Digraph::template ArcMap<Capacity> FlowMap;
/// The type of the potential map.
typedef typename Digraph::template NodeMap<Cost> PotentialMap;
/// \brief Special implementation of the \ref Dijkstra algorithm
/// for finding shortest paths in the residual network.
/// \ref ResidualDijkstra is a special implementation of the
/// \ref Dijkstra algorithm for finding shortest paths in the
/// residual network of the digraph with respect to the reduced arc
/// costs and modifying the node potentials according to the
/// distance of the nodes.
typedef typename Digraph::template NodeMap<int> HeapCrossRef;
typedef BinHeap<Cost, HeapCrossRef> Heap;
// The digraph the algorithm runs on
const CapacityArcMap &_res_cap;
const SupplyNodeMap &_excess;
PotentialMap &_potential;
// The processed (i.e. permanently labeled) nodes
std::vector<Node> _proc_nodes;
ResidualDijkstra( const Digraph &digraph,
const CapacityArcMap &res_cap,
_graph(digraph), _flow(flow), _res_cap(res_cap), _cost(cost),
_excess(excess), _potential(potential), _dist(digraph),
/// Run the algorithm from the given source node.
Node run(Node s, Capacity delta = 1) {
HeapCrossRef heap_cross_ref(_graph, Heap::PRE_HEAP);
Heap heap(heap_cross_ref);
while (!heap.empty() && _excess[heap.top()] > -delta) {
Cost d = heap.prio() + _potential[u], nd;
_proc_nodes.push_back(u);
// Traversing outgoing arcs
for (OutArcIt e(_graph, u); e != INVALID; ++e) {
if (_res_cap[e] >= delta) {
heap.push(v, d + _cost[e] - _potential[v]);
nd = d + _cost[e] - _potential[v];
// Traversing incoming arcs
for (InArcIt e(_graph, u); e != INVALID; ++e) {
heap.push(v, d - _cost[e] - _potential[v]);
nd = d - _cost[e] - _potential[v];
if (heap.empty()) return INVALID;
// Updating potentials of processed nodes
Cost t_dist = heap.prio();
for (int i = 0; i < int(_proc_nodes.size()); ++i)
_potential[_proc_nodes[i]] += _dist[_proc_nodes[i]] - t_dist;
}; //class ResidualDijkstra
// The digraph the algorithm runs on
// The original lower bound map
// The modified capacity map
CapacityArcMap _capacity;
// The modified supply map
// Arc map of the current flow
// Node map of the current potentials
PotentialMap *_potential;
// The residual capacity map
// The excess nodes (i.e. nodes with positive excess)
std::vector<Node> _excess_nodes;
// The deficit nodes (i.e. nodes with negative excess)
std::vector<Node> _deficit_nodes;
// The delta parameter used for capacity scaling
// The maximum number of phases
// Implementation of the Dijkstra algorithm for finding augmenting
// shortest paths in the residual network
ResidualDijkstra *_dijkstra;
/// \brief General constructor (with lower bounds).
/// General constructor (with lower bounds).
/// \param digraph The digraph the algorithm runs on.
/// \param lower The lower bounds of the arcs.
/// \param capacity The capacities (upper bounds) of the arcs.
/// \param cost The cost (length) values of the arcs.
/// \param supply The supply values of the nodes (signed).
CapacityScaling( const Digraph &digraph,
const CapacityMap &capacity,
const SupplyMap &supply ) :
_graph(digraph), _lower(&lower), _capacity(digraph), _cost(cost),
_supply(digraph), _flow(NULL), _local_flow(false),
_potential(NULL), _local_potential(false),
_res_cap(digraph), _excess(digraph), _pred(digraph), _dijkstra(NULL)
for (NodeIt n(_graph); n != INVALID; ++n) {
_valid_supply = sum == 0;
for (ArcIt a(_graph); a != INVALID; ++a) {
_capacity[a] = capacity[a];
_res_cap[a] = capacity[a];
// Remove non-zero lower bounds
typename LowerMap::Value lcap;
for (ArcIt e(_graph); e != INVALID; ++e) {
if ((lcap = lower[e]) != 0) {
_supply[_graph.source(e)] -= lcap;
_supply[_graph.target(e)] += lcap;
_excess[_graph.source(e)] -= lcap;
_excess[_graph.target(e)] += lcap;
/// \brief General constructor (without lower bounds).
/// General constructor (without lower bounds).
/// \param digraph The digraph the algorithm runs on.
/// \param capacity The capacities (upper bounds) of the arcs.
/// \param cost The cost (length) values of the arcs.
/// \param supply The supply values of the nodes (signed).
CapacityScaling( const Digraph &digraph,
const CapacityMap &capacity,
const SupplyMap &supply ) :
_graph(digraph), _lower(NULL), _capacity(capacity), _cost(cost),
_supply(supply), _flow(NULL), _local_flow(false),
_potential(NULL), _local_potential(false),
_res_cap(capacity), _excess(supply), _pred(digraph), _dijkstra(NULL)
// Check the sum of supply values
for (NodeIt n(_graph); n != INVALID; ++n) sum += _supply[n];
_valid_supply = sum == 0;
/// \brief Simple constructor (with lower bounds).
/// Simple constructor (with lower bounds).
/// \param digraph The digraph the algorithm runs on.
/// \param lower The lower bounds of the arcs.
/// \param capacity The capacities (upper bounds) of the arcs.
/// \param cost The cost (length) values of the arcs.
/// \param s The source node.
/// \param t The target node.
/// \param flow_value The required amount of flow from node \c s
/// to node \c t (i.e. the supply of \c s and the demand of \c t).
CapacityScaling( const Digraph &digraph,
const CapacityMap &capacity,
_graph(digraph), _lower(&lower), _capacity(capacity), _cost(cost),
_supply(digraph, 0), _flow(NULL), _local_flow(false),
_potential(NULL), _local_potential(false),
_res_cap(capacity), _excess(digraph, 0), _pred(digraph), _dijkstra(NULL)
// Remove non-zero lower bounds
_supply[s] = _excess[s] = flow_value;
_supply[t] = _excess[t] = -flow_value;
typename LowerMap::Value lcap;
for (ArcIt e(_graph); e != INVALID; ++e) {
if ((lcap = lower[e]) != 0) {
_supply[_graph.source(e)] -= lcap;
_supply[_graph.target(e)] += lcap;
_excess[_graph.source(e)] -= lcap;
_excess[_graph.target(e)] += lcap;
/// \brief Simple constructor (without lower bounds).
/// Simple constructor (without lower bounds).
/// \param digraph The digraph the algorithm runs on.
/// \param capacity The capacities (upper bounds) of the arcs.
/// \param cost The cost (length) values of the arcs.
/// \param s The source node.
/// \param t The target node.
/// \param flow_value The required amount of flow from node \c s
/// to node \c t (i.e. the supply of \c s and the demand of \c t).
CapacityScaling( const Digraph &digraph,
const CapacityMap &capacity,
_graph(digraph), _lower(NULL), _capacity(capacity), _cost(cost),
_supply(digraph, 0), _flow(NULL), _local_flow(false),
_potential(NULL), _local_potential(false),
_res_cap(capacity), _excess(digraph, 0), _pred(digraph), _dijkstra(NULL)
_supply[s] = _excess[s] = flow_value;
_supply[t] = _excess[t] = -flow_value;
if (_local_flow) delete _flow;
if (_local_potential) delete _potential;
/// \brief Set the flow map.
CapacityScaling& flowMap(FlowMap &map) {
/// \brief Set the potential map.
/// Set the potential map.
CapacityScaling& potentialMap(PotentialMap &map) {
_local_potential = false;
/// \name Execution control
/// \brief Run the algorithm.
/// This function runs the algorithm.
/// \param scaling Enable or disable capacity scaling.
/// If the maximum arc capacity and/or the amount of total supply
/// is rather small, the algorithm could be slightly faster without
/// \return \c true if a feasible flow can be found.
bool run(bool scaling = true) {
return init(scaling) && start();
/// \name Query Functions
/// The results of the algorithm can be obtained using these
/// \ref lemon::CapacityScaling::run() "run()" must be called before
/// \brief Return a const reference to the arc map storing the
/// Return a const reference to the arc map storing the found flow.
/// \pre \ref run() must be called before using this function.
const FlowMap& flowMap() const {
/// \brief Return a const reference to the node map storing the
/// found potentials (the dual solution).
/// Return a const reference to the node map storing the found
/// potentials (the dual solution).
/// \pre \ref run() must be called before using this function.
const PotentialMap& potentialMap() const {
/// \brief Return the flow on the given arc.
/// Return the flow on the given arc.
/// \pre \ref run() must be called before using this function.
Capacity flow(const Arc& arc) const {
/// \brief Return the potential of the given node.
/// Return the potential of the given node.
/// \pre \ref run() must be called before using this function.
Cost potential(const Node& node) const {
return (*_potential)[node];
/// \brief Return the total cost of the found flow.
/// Return the total cost of the found flow. The complexity of the
/// function is \f$ O(e) \f$.
/// \pre \ref run() must be called before using this function.
for (ArcIt e(_graph); e != INVALID; ++e)
c += (*_flow)[e] * _cost[e];
/// Initialize the algorithm.
bool init(bool scaling) {
if (!_valid_supply) return false;
_flow = new FlowMap(_graph);
_potential = new PotentialMap(_graph);
for (ArcIt e(_graph); e != INVALID; ++e) (*_flow)[e] = 0;
for (NodeIt n(_graph); n != INVALID; ++n) (*_potential)[n] = 0;
_dijkstra = new ResidualDijkstra( _graph, *_flow, _res_cap, _cost,
_excess, *_potential, _pred );
// Initializing delta value
Supply max_sup = 0, max_dem = 0;
for (NodeIt n(_graph); n != INVALID; ++n) {
if ( _supply[n] > max_sup) max_sup = _supply[n];
if (-_supply[n] > max_dem) max_dem = -_supply[n];
for (ArcIt e(_graph); e != INVALID; ++e) {
if (_capacity[e] > max_cap) max_cap = _capacity[e];
max_sup = std::min(std::min(max_sup, max_dem), max_cap);
for (_delta = 1; 2 * _delta <= max_sup; _delta *= 2)
return startWithScaling();
return startWithoutScaling();
/// Execute the capacity scaling algorithm.
bool startWithScaling() {
// Processing capacity scaling phases
// Saturating all arcs not satisfying the optimality condition
for (ArcIt e(_graph); e != INVALID; ++e) {
Node u = _graph.source(e), v = _graph.target(e);
Cost c = _cost[e] + (*_potential)[u] - (*_potential)[v];
if (c < 0 && _res_cap[e] >= _delta) {
_excess[u] -= _res_cap[e];
_excess[v] += _res_cap[e];
(*_flow)[e] = _capacity[e];
else if (c > 0 && (*_flow)[e] >= _delta) {
_excess[u] += (*_flow)[e];
_excess[v] -= (*_flow)[e];
_res_cap[e] = _capacity[e];
// Finding excess nodes and deficit nodes
for (NodeIt n(_graph); n != INVALID; ++n) {
if (_excess[n] >= _delta) _excess_nodes.push_back(n);
if (_excess[n] <= -_delta) _deficit_nodes.push_back(n);
int next_node = 0, next_def_node = 0;
// Finding augmenting shortest paths
while (next_node < int(_excess_nodes.size())) {
// Checking deficit nodes
bool delta_deficit = false;
for ( ; next_def_node < int(_deficit_nodes.size());
if (_excess[_deficit_nodes[next_def_node]] <= -_delta) {
if (!delta_deficit) break;
s = _excess_nodes[next_node];
if ((t = _dijkstra->run(s, _delta)) == INVALID) {
// Augmenting along a shortest path from s to t.
Capacity d = std::min(_excess[s], -_excess[t]);
while ((e = _pred[u]) != INVALID) {
if (u == _graph.target(e)) {
while ((e = _pred[u]) != INVALID) {
if (u == _graph.target(e)) {
if (_excess[s] < _delta) ++next_node;
if (++phase_cnt > _phase_num / 4) factor = 2;
_delta = _delta <= factor ? 1 : _delta / factor;
// Handling non-zero lower bounds
for (ArcIt e(_graph); e != INVALID; ++e)
(*_flow)[e] += (*_lower)[e];
/// Execute the successive shortest path algorithm.
bool startWithoutScaling() {
for (NodeIt n(_graph); n != INVALID; ++n)
if (_excess[n] > 0) _excess_nodes.push_back(n);
if (_excess_nodes.size() == 0) return true;
// Finding shortest paths
while ( _excess[_excess_nodes[next_node]] > 0 ||
++next_node < int(_excess_nodes.size()) )
s = _excess_nodes[next_node];
if ((t = _dijkstra->run(s)) == INVALID) return false;
// Augmenting along a shortest path from s to t
Capacity d = std::min(_excess[s], -_excess[t]);
while ((e = _pred[u]) != INVALID) {
if (u == _graph.target(e)) {
while ((e = _pred[u]) != INVALID) {
if (u == _graph.target(e)) {
// Handling non-zero lower bounds
for (ArcIt e(_graph); e != INVALID; ++e)
(*_flow)[e] += (*_lower)[e];
}; //class CapacityScaling
#endif //LEMON_CAPACITY_SCALING_H