#include <iostream>
#include "flopc.hpp"
#include <cstdlib>
#include <vector>
#include <time.h>

using namespace std;
using namespace flopc;
#include <OsiCbcSolverInterface.hpp>

/*#define cbc
//#define glpk

#ifdef cbc
	#include <OsiCbcSolverInterface.hpp>
	#define OsiXSolverInterface OsiCbcSolverInterface
#endif 
#ifdef glpk
	#include <OsiGlpkSolverInterface.hpp>
	#define OsiXSolverInterface OsiGlpkSolverInterface
#endif 
/*#ifdef sym
	#include <OsiSymSolverInterface.hpp>
#endif
#ifdef cpx
	#include <OsiCpxSolverInterface.hpp>
#endif */


int main() {    
      
     
    
    MP_model &modello = MP_model::getDefaultModel();
    OsiCbcSolverInterface* pSolver;
    
    pSolver==new OsiCbcSolverInterface;
    modello.Solver=pSolver;
    //modello.Solver=new OsiCbcSolverInterface;
    
    
    pSolver->getModelPtr()->setLogLevel(0); 
    
    modello.silent(); //Short
		//modello.verbose(); //Extended
    
    int nbin = 200;//num var bin
    int nreal = 50;//num var reali
    int nsetcov = 175;//jnum vincoli di setcovering
		int nvarinsetcov = 5;//num var nei vincoli di set covering
		int nlin = 30;//num vincoli lineari
		int M = 1000;//coefficiente di x per rendere banalmente soddisfatti i vincoli lineari
		
    MP_set NBIN(nbin);
    MP_set NRE(nreal);
    
    MP_variable x(NBIN);//dichiaro variabili intere
    x.integer();
    
    MP_variable z(NRE);//dichiaro variabili reali
   				
		vector<MP_constraint*> ArrayBound;
		int j;
		for(j=0; j<nbin; j++)//Upper bound
		{
			ArrayBound.push_back(new MP_constraint);
			*ArrayBound[j]= x(j) <=1;
			modello.add(*ArrayBound[j]);
		}
		/*for(j=0; j<nbin; j++)//Lower bound (sono >= 0 senza necessità di aggiungere il bound, vale anche per le var reali)
		{
			ArrayBound.push_back(new MP_constraint);
			*ArrayBound[j+nbin]= x(j) >=-1;
		}*/
				
		
		int rdx;	
				
		vector<MP_constraint*> ArrayConstraint;		
		MP_expression lista;
		int i;
		for(j=0; j<nsetcov; j++)//inserisco i vincoli di set covering
		{
			rdx = (j + rand()) % nbin;
			cout<<rdx<<" "; 
			lista = x(rdx);
			for(i=1; i<nvarinsetcov; i++)
			{
  			//srand(time(NULL));
  			rdx = (j + rand()) % nbin;
  			cout<<rdx<<" ";     
  			lista = lista + x(rdx);
			}
			ArrayConstraint.push_back(new MP_constraint);
			*ArrayConstraint[j]= lista >=1;
			cout<<endl;
			modello.add(*ArrayConstraint[j]);
		}
				
		
		vector<MP_constraint*> ArrayConstraintLin;	
		MP_expression listalin;	
		int rdz1,rdz2,rdzn;
		for(j=0; j<nlin; j++)//inserisco gli altri vincoli lineari
		{
				rdz1 = 0 + rand() % nlin;
				rdz2 = 0 + rand() % nlin;
				rdx = 0 + rand() % nbin;
				rdzn = 10 + rand() % 20;
				cout<<"Vincolo lin: "<<j;
				cout<<"  z"<<rdz1<<"-z"<<rdz2<<"+"<<M<<"x"<<rdx<<">="<<rdzn<<endl;;
				listalin = z(rdz1)-z(rdz2)+M*x(rdx);
				ArrayConstraintLin.push_back(new MP_constraint);
				*ArrayConstraintLin[j] = listalin >= rdzn;
				modello.add(*ArrayConstraintLin[j]);
		}		
		    
    MP_expression Fob;
    Fob = x(0);
    for(j=1; j<nbin; j++)
    	Fob = Fob + x(j);    
    
    /*for(j=0; j<nlin; j++)
    	Fob = Fob + z(j); */ 
   
    modello.minimize( Fob );
   
    modello->writeMps("test");//scrive il modello sul file mps
    cout<<"Optimal solution per x:"<<endl;
    for(j=0; j<nbin; j++)
    	cout<<"x("<<j<<")="<<x.level(j)<<" ";
    cout<<endl;
    for(j=0; j<nlin; j++)
    	cout<<"z("<<j<<")="<<z.level(j)<<" ";
    cout<<endl;
        
}