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/* -*- C++ -*-
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*
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* This file is a part of LEMON, a generic C++ optimization library
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*
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* Copyright (C) 2003-2007
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* Egervary Jeno Kombinatorikus Optimalizalasi Kutatocsoport
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* (Egervary Research Group on Combinatorial Optimization, EGRES).
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*
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* Permission to use, modify and distribute this software is granted
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* provided that this copyright notice appears in all copies. For
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* precise terms see the accompanying LICENSE file.
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*
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* This software is provided "AS IS" with no warranty of any kind,
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* express or implied, and with no claim as to its suitability for any
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* purpose.
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*
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*/
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#ifndef LEMON_CSP_H
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#define LEMON_CSP_H
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///\ingroup approx
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///\file
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///\brief Algorithm for the Resource Constrained Shortest Path problem.
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///
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///
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///\todo dijkstraZero() solution should be revised.
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#include <lemon/list_graph.h>
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#include <lemon/graph_utils.h>
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#include <lemon/error.h>
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#include <lemon/maps.h>
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#include <lemon/tolerance.h>
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#include <lemon/dijkstra.h>
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#include <lemon/path.h>
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#include <lemon/counter.h>
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namespace lemon {
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///\ingroup approx
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///Algorithms for the Resource Constrained Shortest Path Problem
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///The Resource Constrained Shortest (Least Cost) Path problem is the
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///following. We are given a directed graph with two additive weightings
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///on the edges, referred as \e cost and \e delay. In addition,
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///a source and a destination node \e s and \e t and a delay
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///constraint \e D is given. A path \e p is called \e feasible
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///if <em>delay(p)\<=D</em>. Then, the task is to find the least cost
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///feasible path.
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///
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template<class Graph,
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class CM=typename Graph:: template EdgeMap<double>,
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class DM=CM>
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class ConstrainedShortestPath
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{
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public:
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GRAPH_TYPEDEFS(typename Graph);
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typedef SimplePath<Graph> Path;
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Graph &_g;
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Tolerance<double> tol;
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CM &_cost;
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DM &_delay;
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class CoMap
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{
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CM &_cost;
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DM &_delay;
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double _lambda;
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public:
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typedef typename CM::Key Key;
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typedef double Value;
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CoMap(CM &c,DM &d) :_cost(c), _delay(d), _lambda(0) {}
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double lambda() const { return _lambda; }
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void lambda(double l) { _lambda=l; }
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Value operator[](Key &e) const
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{
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return _cost[e]+_lambda*_delay[e];
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}
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} _co_map;
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Dijkstra<Graph, CoMap> _dij;
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///\e
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///\e
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///
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ConstrainedShortestPath(Graph &g, CM &ct, DM &dl)
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: _g(g), _cost(ct), _delay(dl),
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_co_map(ct,dl), _dij(_g,_co_map) {}
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///Compute the cost of a path
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double cost(const Path &p)
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{
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double s=0;
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// Path r;
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for(typename Path::EdgeIt e(p);e!=INVALID;++e) s+=_cost[e];
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return s;
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}
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///Compute the delay of a path
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double delay(const Path &p)
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{
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double s=0;
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for(typename Path::EdgeIt e(p);e!=INVALID;++e) s+=_delay[e];
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return s;
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}
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///Runs the LARAC algorithm
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///This function runs a Lagrange relaxation based heuristic to find
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///a delay constrained least cost path.
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///\param s source node
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///\param t target node
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///\retval lo_bo a lower bound on the optimal solution
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///\return the found path or an empty
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Path larac(Node s, Node t, double delta, double &lo_bo)
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{
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NoCounter cnt("LARAC iterations: ");
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double lambda=0;
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double cp,cq,dp,dq,cr,dr;
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Path p;
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Path q;
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Path r;
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{
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Dijkstra<Graph,CM> dij(_g,_cost);
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dij.run(s,t);
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cnt++;
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if(!dij.reached(t)) return Path();
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p=dij.path(t);
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cp=cost(p);
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dp=delay(p);
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}
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if(delay(p)<=delta) return p;
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{
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Dijkstra<Graph,DM> dij(_g,_delay);
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dij.run(s,t);
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cnt++;
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q=dij.path(t);
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cq=cost(q);
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dq=delay(q);
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}
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if(delay(q)>delta) return Path();
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while (true) {
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lambda=(cp-cq)/(dq-dp);
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_co_map.lambda(lambda);
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_dij.run(s,t);
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cnt++;
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r=_dij.path(t);
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cr=cost(r);
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dr=delay(r);
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if(!tol.less(cr+lambda*dr,cp+lambda*dp)) {
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lo_bo=cq+lambda*(dq-delta);
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return q;
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}
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else if(tol.less(dr,delta))
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{
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q=r;
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cq=cr;
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dq=dr;
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}
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else if(tol.less(delta,dr))
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{
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p=r;
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cp=cr;
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dp=dr;
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}
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else return r;
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}
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}
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};
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} //END OF NAMESPACE LEMON
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#endif
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