MP_model.cpp

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// ******************** FlopCpp **********************************************
// File: MP_model.cpp
// $Id$
// Author: Tim Helge Hultberg (thh@mat.ua.pt)
// Copyright (C) 2003 Tim Helge Hultberg
// All Rights Reserved.
//****************************************************************************

#include <iostream>
#include <sstream>
#include <algorithm>

#include <CoinPackedMatrix.hpp>
#include <OsiSolverInterface.hpp>
#include "MP_model.hpp"
#include "MP_variable.hpp"
#include "MP_constraint.hpp"
#include <CoinTime.hpp>

using namespace flopc;
using namespace std;

MP_model& MP_model::default_model = *new MP_model(0);
MP_model* MP_model::current_model = &MP_model::default_model;
MP_model &MP_model::getDefaultModel() { return default_model;}
MP_model *MP_model::getCurrentModel() { return current_model;}

void NormalMessenger::statistics(int bm, int m, int bn, int n, int nz) {
    cout<<"FlopCpp: Number of constraint blocks: " <<bm<<endl;
    cout<<"FlopCpp: Number of individual constraints: " <<m<<endl;
    cout<<"FlopCpp: Number of variable blocks: " <<bn<<endl;
    cout<<"FlopCpp: Number of individual variables: " <<n<<endl;
    cout<<"FlopCpp: Number of non-zeroes (including rhs): " <<nz<<endl;
}

void NormalMessenger::generationTime(double t) {
    cout<<"FlopCpp: Generation time: "<<t<<endl;
}

void VerboseMessenger::constraintDebug(string name, const vector<Coef>& cfs) {
    cout<<"FlopCpp: Constraint "<<name<<endl;
    for (unsigned int j=0; j<cfs.size(); j++) {
        int col=cfs[j].col;
        int row=cfs[j].row;
        double elm=cfs[j].val;
        int stage=cfs[j].stage;
        cout<<row<<"   "<<col<<"  "<<elm<<"  "<<stage<<endl;
    }
}

void VerboseMessenger::objectiveDebug(const vector<Coef>& cfs) {
    cout<<"Objective "<<endl;
    for (unsigned int j=0; j<cfs.size(); j++) {
        int col=cfs[j].col;
        int row=cfs[j].row;
        double elm=cfs[j].val;
        cout<<row<<"   "<<col<<"  "<<elm<<endl;
    }
}

MP_model::MP_model(OsiSolverInterface* s, Messenger* m) : 
    solution(0), messenger(m), Objective(0), Solver(s), 
    m(0), n(0), nz(0), bl(0),
    mSolverState(((s==NULL)?(MP_model::DETACHED):(MP_model::SOLVER_ONLY))) {
    MP_model::current_model = this;
}

MP_model& MP_model::add(MP_constraint& lcl_c) {
    Constraints.insert(&lcl_c);
    return *this;
}

void MP_model::add(MP_constraint* lcl_c) {
    lcl_c->M = this;
    lcl_c->offset = m;
    m += lcl_c->size();
}

double MP_model::getInfinity() const {
    if (Solver==0) {
        return 9.9e+32;
    } else {
        return Solver->getInfinity();
    }
}

void MP_model::add(MP_variable* v) {
    v->M = this;
    v->offset = n;
    n += v->size();
}

void MP_model::addRow(const Constraint& lcl_c) {
    vector<Coef> cfs;
    vector<Constant> v;
    ObjectiveGenerateFunctor f(cfs);
    lcl_c.left->generate(MP_domain::getEmpty(),v,f,1.0);
    lcl_c.right->generate(MP_domain::getEmpty(),v,f,-1.0);
    CoinPackedVector newRow;
    double rhs = 0.0;
    for (unsigned int j=0; j<cfs.size(); j++) {
        int col=cfs[j].col;
        //int row=cfs[j].row;
        double elm=cfs[j].val;
        //cout<<row<<"   "<<col<<"  "<<elm<<endl;
        if (col>=0) {
            newRow.insert(col,elm);
        } else if (col==-1) {
            rhs = elm;
        }
    }
    // NB no "assembly" of added row yet. Will be done....
 
    double lcl_bl = -rhs;
    double lcl_bu = -rhs;

    double inf = Solver->getInfinity();
    switch (lcl_c.sense) {
        case LE:
            lcl_bl = - inf;
            break;
        case GE:
            lcl_bu = inf;
            break;
        case EQ:
            // Nothing to do
            break;              
    }

    Solver->addRow(newRow,lcl_bl,lcl_bu);
}

void MP_model::setObjective(const MP_expression& o) { 
    Objective = o; 
}

void MP_model::minimize_max(MP_set &s, const MP_expression  &obj) {
    MP_variable v;
    MP_constraint lcl_c(s);
    add(lcl_c);
    lcl_c(s) = v() >= obj;
    minimize(v());
} 


class flopc::CoefLess {
public:
    bool operator() (const Coef& a, const Coef& b) const {
        if (a.col < b.col) {
            return true;
        } else if (a.col == b.col && a.row < b.row) {
            return true;
        } else {
            return false;
        }
    }
};

void MP_model::assemble(vector<Coef>& v, vector<Coef>& av) {
    std::sort(v.begin(),v.end(),CoefLess());
    int c,r,s;
    double val;
    std::vector<Coef>::const_iterator i = v.begin();
    while (i!=v.end()) {
        c = i->col;
        r = i->row;
        val = i->val;
        s = i->stage;
        i++;
        while (i!=v.end() && c==i->col && r==i->row) {
            val += i->val;
            if (i->stage>s) {
                s = i->stage;
            }
            i++;
        }
        av.push_back(Coef(c,r,val,s));
    }
}

void MP_model::maximize() {
    if (Solver!=0) {
        attach(Solver);
        solve(MP_model::MAXIMIZE);
    } else {
        cout<<"no solver specified"<<endl;
    }
}

void MP_model::maximize(const MP_expression &obj) {
    if (Solver!=0) {
        Objective = obj;
        attach(Solver);
        solve(MP_model::MAXIMIZE);
    } else {
        cout<<"no solver specified"<<endl;
    }
}

void MP_model::minimize() {
    if (Solver!=0) {
        attach(Solver);
        solve(MP_model::MINIMIZE);
    } else {
        cout<<"no solver specified"<<endl;
    }
}

void MP_model::minimize(const MP_expression &obj) {
    if (Solver!=0) {
        Objective = obj;
        attach(Solver);
        solve(MP_model::MINIMIZE);
    } else {
        cout<<"no solver specified"<<endl;
    }
}

void MP_model::attach(OsiSolverInterface *_solver) {
    if (_solver==NULL) {
        if (Solver==NULL) {
            mSolverState = MP_model::DETACHED;
            return;
        }  
    } else {  // use pre-attached solver.
        if(Solver && Solver!=_solver) {
            detach();
        }
        Solver=_solver;
    }
    double time = CoinCpuTime();
    m=0;
    n=0;
    vector<Coef> coefs;
    vector<Coef> cfs;

    typedef std::set<MP_variable* >::iterator varIt;
    typedef std::set<MP_constraint* >::iterator conIt;
    
    Objective->insertVariables(Variables);
    for (conIt i=Constraints.begin(); i!=Constraints.end(); i++) {
        add(*i);
        (*i)->insertVariables(Variables);
    }
    for (varIt j=Variables.begin(); j!=Variables.end(); j++) {
        add(*j);
    }

    // Generate coefficient matrix and right hand side
    bool doAssemble = true;
    if (doAssemble == true) {
        GenerateFunctor f(cfs);
        for (conIt i=Constraints.begin(); i!=Constraints.end(); i++) {
            (*i)->coefficients(f);
            messenger->constraintDebug((*i)->getName(),cfs);
            assemble(cfs,coefs);
            cfs.erase(cfs.begin(),cfs.end());
        }
    } else {
        GenerateFunctor f(coefs);
        for (conIt i=Constraints.begin(); i!=Constraints.end(); i++) {
            (*i)->coefficients(f);
        }
    }
    nz = static_cast<int>(coefs.size());

    messenger->statistics(static_cast<int>(Constraints.size()),m,static_cast<int>(Variables.size()),n,nz);

    Elm = new double[nz]; 
    Rnr = new int[nz];    
    Cst = new int[n+2];   
    Clg = new int[n+1];   
    l =   new double[n];  
    u =   new double[n];  
    bl  = new double[m];  
    bu  = new double[m];  

    const double inf = Solver->getInfinity();

    for (int j=0; j<n; j++) {
        Clg[j] = 0;
    }
    Clg[n] = 0;
    
    // Treat right hand side as n'th column
    for (int j=0; j<=n; j++) {
        Clg[j] = 0;
    }
    for (int i=0; i<nz; i++) {
        int col = coefs[i].col;
        if (col == -1)  {
            col = n;
        }
        Clg[col]++;
    }
    Cst[0]=0;
    for (int j=0; j<=n; j++) {
        Cst[j+1]=Cst[j]+Clg[j]; 
    }
    for (int i=0; i<=n; i++) {
        Clg[i]=0;
    }
    for (int i=0; i<nz; i++) {
        int col = coefs[i].col;
        if (col==-1) {
            col = n;
        }
        int row = coefs[i].row;
        double elm = coefs[i].val;
        Elm[Cst[col]+Clg[col]] = elm;
        Rnr[Cst[col]+Clg[col]] = row;
        Clg[col]++;
    }

    // Row bounds
    for (int i=0; i<m; i++) {
        bl[i] = 0;
        bu[i] = 0;
    }
    for (int j=Cst[n]; j<Cst[n+1]; j++) {
        bl[Rnr[j]] = -Elm[j];
        bu[Rnr[j]] = -Elm[j];
    }

    for (conIt i=Constraints.begin(); i!=Constraints.end(); i++) {
        int begin = (*i)->offset;
        int end = (*i)->offset+(*i)->size();
        switch ((*i)->sense) {
            case LE:
                for (int k=begin; k<end; k++) {
                    bl[k] = - inf;
                } 
                break;
            case GE:
                for (int k=begin; k<end; k++) {
                    bu[k] = inf;
                }       
                break;
            case EQ:
                // Nothing to do
                break;          
        }
    }

    // Generate objective function coefficients
    vector<Constant> v;
    if (doAssemble == true) {
        ObjectiveGenerateFunctor f(cfs);
        coefs.erase(coefs.begin(),coefs.end());
        Objective->generate(MP_domain::getEmpty(), v, f, 1.0);

        messenger->objectiveDebug(cfs);
        assemble(cfs,coefs);
    } else {
        ObjectiveGenerateFunctor f(coefs);
        coefs.erase(coefs.begin(),coefs.end());
        Objective->generate(MP_domain::getEmpty(), v, f, 1.0);
    }   

    c =  new double[n]; 
    for (int j=0; j<n; j++) {
        c[j] = 0.0;
    }
    for (size_t i=0; i<coefs.size(); i++) {
        int col = coefs[i].col;
        double elm = coefs[i].val;
        c[col] = elm;
    } 

    // Column bounds
    for (int j=0; j<n; j++) {
        l[j] = 0.0;
        u[j] = inf;
    }

    for (varIt i=Variables.begin(); i!=Variables.end(); i++) {
        for (int k=0; k<(*i)->size(); k++) {
            l[(*i)->offset+k] = (*i)->lowerLimit.v[k];
            u[(*i)->offset+k] = (*i)->upperLimit.v[k];
        }
    }

    CoinPackedMatrix A(true,m,n,Cst[n],Elm,Rnr,Cst,Clg);
    Solver->loadProblem(A, l, u, c, bl, bu);

    // Instead of the 2 lines above we should be able to use
    // the line below, but due to a bug in OsiGlpk it does not work
    // Solver->loadProblem(n, m, Cst, Rnr, Elm, l, u, c, bl, bu);

    delete [] Elm; 
    delete [] Rnr;    
    delete [] Cst;   
    delete [] Clg;   
    delete [] l;  
    delete [] u;  
    delete [] bl;  
    delete [] bu;  
    delete [] c;
    
    for (varIt i=Variables.begin(); i!=Variables.end(); i++) {
        int begin = (*i)->offset;
        int end = (*i)->offset+(*i)->size();
        if ((*i)->type == discrete) {
            for (int k=begin; k<end; k++) {
                Solver->setInteger(k);
            }
        }
    }
    mSolverState = MP_model::ATTACHED;
    messenger->generationTime(time-CoinCpuTime());

}
void MP_model::detach() {
    assert(Solver);
    mSolverState=MP_model::DETACHED;
    delete Solver;
    Solver=NULL;
}

MP_model::MP_status MP_model::solve(const MP_model::MP_direction &dir) {
    assert(Solver);
    assert(mSolverState != MP_model::DETACHED && 
           mSolverState != MP_model::SOLVER_ONLY);
    Solver->setObjSense(dir);
    bool isMIP = false;
    for (varIt i=Variables.begin(); i!=Variables.end(); i++) {
        if ((*i)->type == discrete) {
            isMIP = true;
            break;
        }
    }
    if (isMIP == true) {
        try {
            Solver->branchAndBound();
        } catch  (CoinError e) {
            cout<<e.message()<<endl;
            cout<<"Solving the LP relaxation instead."<<endl;
            try {
                Solver->initialSolve();
            } catch (CoinError e) {
                cout<<e.message()<<endl;
            }
        }
    } else {
        try {
            Solver->initialSolve();
        }  catch (CoinError e) {
            cout<<e.message()<<endl;
        }
    }
     
    if (Solver->isProvenOptimal() == true) {
        cout<<"FlopCpp: Optimal obj. value = "<<Solver->getObjValue()<<endl;
        cout<<"FlopCpp: Solver(m, n, nz) = "<<Solver->getNumRows()<<"  "<<
            Solver->getNumCols()<<"  "<<Solver->getNumElements()<<endl;
        solution = Solver->getColSolution();
        reducedCost = Solver->getReducedCost();
        rowPrice = Solver->getRowPrice();
        rowActivity = Solver->getRowActivity();
    } else if (Solver->isProvenPrimalInfeasible() == true) {
        return mSolverState=MP_model::PRIMAL_INFEASIBLE;
        //cout<<"FlopCpp: Problem is primal infeasible."<<endl;
    } else if (Solver->isProvenDualInfeasible() == true) {
        return mSolverState=MP_model::DUAL_INFEASIBLE;
        //cout<<"FlopCpp: Problem is dual infeasible."<<endl;
    } else {
        return mSolverState=MP_model::ABANDONED;
        //cout<<"FlopCpp: Solution process abandoned."<<endl;
    }
    return mSolverState=MP_model::OPTIMAL;
}

namespace flopc {
    std::ostream &operator<<(std::ostream &os, 
                             const MP_model::MP_status &condition) {
        switch(condition) {
            case MP_model::OPTIMAL:
                os<<"OPTIMAL";
                break;
            case MP_model::PRIMAL_INFEASIBLE:
                os<<"PRIMAL_INFEASIBLE";
                break;
            case MP_model::DUAL_INFEASIBLE:
                os<<"DUAL_INFEASIBLE";
                break;
            case MP_model::ABANDONED:
                os<<"ABANDONED";
                break;
            default:
                os<<"UNKNOWN";
        };
        return os;
    }

    std::ostream &operator<<(std::ostream &os, 
                             const MP_model::MP_direction &direction) {
        switch(direction) {
            case MP_model::MINIMIZE:
                os<<"MINIMIZE";
                break;
            case MP_model::MAXIMIZE:
                os<<"MAXIMIZE";
                break;
            default:
                os<<"UNKNOWN";
        };
        return os;
    }
}