Location: LEMON/LEMON-main/lemon/capacity_scaling.h - annotation
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Port CapacityScaling from SVN -r3524 (#180)
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*
* 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
* purpose.
*
*/
#ifndef LEMON_CAPACITY_SCALING_H
#define LEMON_CAPACITY_SCALING_H
/// \ingroup min_cost_flow
///
/// \file
/// \brief Capacity scaling algorithm for finding a minimum cost flow.
#include <vector>
#include <lemon/bin_heap.h>
namespace lemon {
/// \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
/// cost flow.
///
/// \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.
///
/// \warning
/// - 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.
///
/// \author Peter Kovacs
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> >
class CapacityScaling
{
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;
public:
/// 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;
private:
/// \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.
class ResidualDijkstra
{
typedef typename Digraph::template NodeMap<int> HeapCrossRef;
typedef BinHeap<Cost, HeapCrossRef> Heap;
private:
// The digraph the algorithm runs on
const Digraph &_graph;
// The main maps
const FlowMap &_flow;
const CapacityArcMap &_res_cap;
const CostMap &_cost;
const SupplyNodeMap &_excess;
PotentialMap &_potential;
// The distance map
PotentialMap _dist;
// The pred arc map
PredMap &_pred;
// The processed (i.e. permanently labeled) nodes
std::vector<Node> _proc_nodes;
public:
/// Constructor.
ResidualDijkstra( const Digraph &digraph,
const FlowMap &flow,
const CapacityArcMap &res_cap,
const CostMap &cost,
const SupplyMap &excess,
PotentialMap &potential,
PredMap &pred ) :
_graph(digraph), _flow(flow), _res_cap(res_cap), _cost(cost),
_excess(excess), _potential(potential), _dist(digraph),
_pred(pred)
{}
/// 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);
heap.push(s, 0);
_pred[s] = INVALID;
_proc_nodes.clear();
// Processing nodes
while (!heap.empty() && _excess[heap.top()] > -delta) {
Node u = heap.top(), v;
Cost d = heap.prio() + _potential[u], nd;
_dist[u] = heap.prio();
heap.pop();
_proc_nodes.push_back(u);
// Traversing outgoing arcs
for (OutArcIt e(_graph, u); e != INVALID; ++e) {
if (_res_cap[e] >= delta) {
v = _graph.target(e);
switch(heap.state(v)) {
case Heap::PRE_HEAP:
heap.push(v, d + _cost[e] - _potential[v]);
_pred[v] = e;
break;
case Heap::IN_HEAP:
nd = d + _cost[e] - _potential[v];
if (nd < heap[v]) {
heap.decrease(v, nd);
_pred[v] = e;
}
break;
case Heap::POST_HEAP:
break;
}
}
}
// Traversing incoming arcs
for (InArcIt e(_graph, u); e != INVALID; ++e) {
if (_flow[e] >= delta) {
v = _graph.source(e);
switch(heap.state(v)) {
case Heap::PRE_HEAP:
heap.push(v, d - _cost[e] - _potential[v]);
_pred[v] = e;
break;
case Heap::IN_HEAP:
nd = d - _cost[e] - _potential[v];
if (nd < heap[v]) {
heap.decrease(v, nd);
_pred[v] = e;
}
break;
case Heap::POST_HEAP:
break;
}
}
}
}
if (heap.empty()) return INVALID;
// Updating potentials of processed nodes
Node t = heap.top();
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;
return t;
}
}; //class ResidualDijkstra
private:
// The digraph the algorithm runs on
const Digraph &_graph;
// The original lower bound map
const LowerMap *_lower;
// The modified capacity map
CapacityArcMap _capacity;
// The original cost map
const CostMap &_cost;
// The modified supply map
SupplyNodeMap _supply;
bool _valid_supply;
// Arc map of the current flow
FlowMap *_flow;
bool _local_flow;
// Node map of the current potentials
PotentialMap *_potential;
bool _local_potential;
// The residual capacity map
CapacityArcMap _res_cap;
// The excess map
SupplyNodeMap _excess;
// 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
Capacity _delta;
// The maximum number of phases
int _phase_num;
// The pred arc map
PredMap _pred;
// Implementation of the Dijkstra algorithm for finding augmenting
// shortest paths in the residual network
ResidualDijkstra *_dijkstra;
public:
/// \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 LowerMap &lower,
const CapacityMap &capacity,
const CostMap &cost,
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)
{
Supply sum = 0;
for (NodeIt n(_graph); n != INVALID; ++n) {
_supply[n] = supply[n];
_excess[n] = supply[n];
sum += supply[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) {
_capacity[e] -= lcap;
_res_cap[e] -= lcap;
_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 CostMap &cost,
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
Supply sum = 0;
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 LowerMap &lower,
const CapacityMap &capacity,
const CostMap &cost,
Node s, Node t,
Supply flow_value ) :
_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) {
_capacity[e] -= lcap;
_res_cap[e] -= lcap;
_supply[_graph.source(e)] -= lcap;
_supply[_graph.target(e)] += lcap;
_excess[_graph.source(e)] -= lcap;
_excess[_graph.target(e)] += lcap;
}
}
_valid_supply = true;
}
/// \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,
const CostMap &cost,
Node s, Node t,
Supply flow_value ) :
_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;
_valid_supply = true;
}
*/
/// Destructor.
~CapacityScaling() {
if (_local_flow) delete _flow;
if (_local_potential) delete _potential;
delete _dijkstra;
}
/// \brief Set the flow map.
///
/// Set the flow map.
///
/// \return \c (*this)
CapacityScaling& flowMap(FlowMap &map) {
if (_local_flow) {
delete _flow;
_local_flow = false;
}
_flow = ↦
return *this;
}
/// \brief Set the potential map.
///
/// Set the potential map.
///
/// \return \c (*this)
CapacityScaling& potentialMap(PotentialMap &map) {
if (_local_potential) {
delete _potential;
_local_potential = false;
}
_potential = ↦
return *this;
}
/// \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
/// scaling.
///
/// \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
/// functions.\n
/// \ref lemon::CapacityScaling::run() "run()" must be called before
/// using them.
/// @{
/// \brief Return a const reference to the arc map storing the
/// found flow.
///
/// 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 {
return *_flow;
}
/// \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 {
return *_potential;
}
/// \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 {
return (*_flow)[arc];
}
/// \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.
Cost totalCost() const {
Cost c = 0;
for (ArcIt e(_graph); e != INVALID; ++e)
c += (*_flow)[e] * _cost[e];
return c;
}
/// @}
private:
/// Initialize the algorithm.
bool init(bool scaling) {
if (!_valid_supply) return false;
// Initializing maps
if (!_flow) {
_flow = new FlowMap(_graph);
_local_flow = true;
}
if (!_potential) {
_potential = new PotentialMap(_graph);
_local_potential = true;
}
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
if (scaling) {
// With scaling
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];
}
Capacity max_cap = 0;
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);
_phase_num = 0;
for (_delta = 1; 2 * _delta <= max_sup; _delta *= 2)
++_phase_num;
} else {
// Without scaling
_delta = 1;
}
return true;
}
bool start() {
if (_delta > 1)
return startWithScaling();
else
return startWithoutScaling();
}
/// Execute the capacity scaling algorithm.
bool startWithScaling() {
// Processing capacity scaling phases
Node s, t;
int phase_cnt = 0;
int factor = 4;
while (true) {
// 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];
_res_cap[e] = 0;
}
else if (c > 0 && (*_flow)[e] >= _delta) {
_excess[u] += (*_flow)[e];
_excess[v] -= (*_flow)[e];
(*_flow)[e] = 0;
_res_cap[e] = _capacity[e];
}
}
// Finding excess nodes and deficit nodes
_excess_nodes.clear();
_deficit_nodes.clear();
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
if (_delta > 1) {
bool delta_deficit = false;
for ( ; next_def_node < int(_deficit_nodes.size());
++next_def_node ) {
if (_excess[_deficit_nodes[next_def_node]] <= -_delta) {
delta_deficit = true;
break;
}
}
if (!delta_deficit) break;
}
// Running Dijkstra
s = _excess_nodes[next_node];
if ((t = _dijkstra->run(s, _delta)) == INVALID) {
if (_delta > 1) {
++next_node;
continue;
}
return false;
}
// Augmenting along a shortest path from s to t.
Capacity d = std::min(_excess[s], -_excess[t]);
Node u = t;
Arc e;
if (d > _delta) {
while ((e = _pred[u]) != INVALID) {
Capacity rc;
if (u == _graph.target(e)) {
rc = _res_cap[e];
u = _graph.source(e);
} else {
rc = (*_flow)[e];
u = _graph.target(e);
}
if (rc < d) d = rc;
}
}
u = t;
while ((e = _pred[u]) != INVALID) {
if (u == _graph.target(e)) {
(*_flow)[e] += d;
_res_cap[e] -= d;
u = _graph.source(e);
} else {
(*_flow)[e] -= d;
_res_cap[e] += d;
u = _graph.target(e);
}
}
_excess[s] -= d;
_excess[t] += d;
if (_excess[s] < _delta) ++next_node;
}
if (_delta == 1) break;
if (++phase_cnt > _phase_num / 4) factor = 2;
_delta = _delta <= factor ? 1 : _delta / factor;
}
// Handling non-zero lower bounds
if (_lower) {
for (ArcIt e(_graph); e != INVALID; ++e)
(*_flow)[e] += (*_lower)[e];
}
return true;
}
/// Execute the successive shortest path algorithm.
bool startWithoutScaling() {
// Finding excess nodes
for (NodeIt n(_graph); n != INVALID; ++n)
if (_excess[n] > 0) _excess_nodes.push_back(n);
if (_excess_nodes.size() == 0) return true;
int next_node = 0;
// Finding shortest paths
Node s, t;
while ( _excess[_excess_nodes[next_node]] > 0 ||
++next_node < int(_excess_nodes.size()) )
{
// Running Dijkstra
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]);
Node u = t;
Arc e;
if (d > 1) {
while ((e = _pred[u]) != INVALID) {
Capacity rc;
if (u == _graph.target(e)) {
rc = _res_cap[e];
u = _graph.source(e);
} else {
rc = (*_flow)[e];
u = _graph.target(e);
}
if (rc < d) d = rc;
}
}
u = t;
while ((e = _pred[u]) != INVALID) {
if (u == _graph.target(e)) {
(*_flow)[e] += d;
_res_cap[e] -= d;
u = _graph.source(e);
} else {
(*_flow)[e] -= d;
_res_cap[e] += d;
u = _graph.target(e);
}
}
_excess[s] -= d;
_excess[t] += d;
}
// Handling non-zero lower bounds
if (_lower) {
for (ArcIt e(_graph); e != INVALID; ++e)
(*_flow)[e] += (*_lower)[e];
}
return true;
}
}; //class CapacityScaling
///@}
} //namespace lemon
#endif //LEMON_CAPACITY_SCALING_H
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