Esempio n. 1
0
int main()
{
    std::cout << "[moeoNSGAII]" << std::endl;

    TestEval eval;
    eoPopLoopEval <Solution> popEval(eval);
    eoQuadCloneOp < Solution > xover;
    eoUniformMutation < Solution > mutation(0.05);

    eoRealVectorBounds bounds(1, 1.0, 2.0);
    eoRealInitBounded < Solution > init(bounds);
    eoPop < Solution > pop(20, init);
    eoQuadGenOp <Solution> genOp(xover);
    eoSGATransform < Solution > transform(xover, 0.1, mutation, 0.1);
    eoGenContinue <Solution > continuator(10);

    // build NSGA-II
    moeoNSGAII < Solution > algo(20, eval, xover, 1.0, mutation, 1.0);
    moeoNSGAII < Solution > algo2(continuator, eval, genOp);
    moeoNSGAII < Solution > algo3(continuator, popEval, genOp);
    moeoNSGAII < Solution > algo4(continuator, eval, transform);
    moeoNSGAII < Solution > algo5(continuator, popEval, transform);

    // run the algo
    algo(pop);

    // final pop
    std::cout << "Final population" << std::endl;
    std::cout << pop << std::endl;

    std::cout << "[moeoNSGAII] OK" << std::endl;
    return EXIT_SUCCESS;
}
Esempio n. 2
0
int main()
{
    std::cout << "[moeoSEEA]" << std::endl;

    TestEval eval;
    eoQuadCloneOp < Solution > xover;
    eoUniformMutation < Solution > mutation(0.05);

    eoRealVectorBounds bounds(2, 1.0, 2.0);
    eoRealInitBounded < Solution > init(bounds);
    eoPop < Solution > pop(20, init);
    eoQuadGenOp <Solution> genOp(xover);
    eoSGATransform < Solution > transform(xover, 0.1, mutation, 0.1);
    eoGenContinue <Solution > continuator(20);
    moeoUnboundedArchive < Solution > archive;

    eoPopLoopEval <Solution> loopEval(eval);
    eoPopEvalFunc <Solution>& popEval(loopEval);

    // build SEEA
    moeoSEEA < Solution > algo1(20, eval, xover, 1.0, mutation, 1.0, archive);
    moeoSEEA < Solution > algo2(continuator, eval, genOp, archive);
    moeoSEEA < Solution > algo3(continuator, popEval, genOp, archive);
    moeoSEEA < Solution > algo4(continuator, eval, transform, archive);
    moeoSEEA < Solution > algo5(continuator, popEval, transform, archive);

    // run the algo
    algo5(pop);

    // final archive
    std::cout << "Final archive" << std::endl;
    std::cout << archive << std::endl;

    std::cout << "[moeoSEEA] OK" << std::endl;
    return EXIT_SUCCESS;
}
Esempio n. 3
0
int main(int argc, char* argv[]) {

  Teuchos::GlobalMPISession mpiSession(&argc, &argv);
  Teuchos::RCP<const Teuchos::Comm<int> > comm
    = Teuchos::DefaultComm<int>::getComm();

  // This little trick lets us print to std::cout only if a (dummy) command-line argument is provided.
  int iprint = argc - 1;
  Teuchos::RCP<std::ostream> outStream;
  Teuchos::oblackholestream bhs; // outputs nothing
  if (iprint > 0 && Teuchos::rank<int>(*comm)==0)
    outStream = Teuchos::rcp(&std::cout, false);
  else
    outStream = Teuchos::rcp(&bhs, false);

  int errorFlag  = 0;

  try {
    /**********************************************************************************************/
    /************************* CONSTRUCT ROL ALGORITHM ********************************************/
    /**********************************************************************************************/
    // Get ROL parameterlist
    std::string filename = "input.xml";
    Teuchos::RCP<Teuchos::ParameterList> parlist = Teuchos::rcp( new Teuchos::ParameterList() );
    Teuchos::updateParametersFromXmlFile( filename, parlist.ptr() );
    RealT initZ = parlist->sublist("Problem Description").get("Initial Control Guess", 0.0);
    RealT cvarLevel = parlist->sublist("Problem Description").get("CVaR Level", 0.8);
    RealT pfuncSmoothing = parlist->sublist("Problem Description").get("Plus Function Smoothing Parameter", 1e-2);
    /**********************************************************************************************/
    /************************* CONSTRUCT VECTORS **************************************************/
    /**********************************************************************************************/
    // Build control vectors
    int nx = 256;
    Teuchos::RCP<std::vector<RealT> > x1_rcp  = Teuchos::rcp( new std::vector<RealT>(nx+2,0.0) );
    //ROL::StdVector<RealT> x1(x1_rcp);
      Teuchos::RCP<ROL::StdVector<RealT> > x1 = Teuchos::rcp(new ROL::StdVector<RealT>(x1_rcp));
    Teuchos::RCP<std::vector<RealT> > x2_rcp  = Teuchos::rcp( new std::vector<RealT>(nx+2,0.0) );
    ROL::StdVector<RealT> x2(x2_rcp);
    Teuchos::RCP<std::vector<RealT> > x3_rcp  = Teuchos::rcp( new std::vector<RealT>(nx+2,0.0) );
    ROL::StdVector<RealT> x3(x3_rcp);
    Teuchos::RCP<std::vector<RealT> > z_rcp  = Teuchos::rcp( new std::vector<RealT>(nx+2,0.0) );
    //ROL::StdVector<RealT> z(z_rcp);
      Teuchos::RCP<ROL::StdVector<RealT> > z = Teuchos::rcp(new ROL::StdVector<RealT>(z_rcp));
    Teuchos::RCP<std::vector<RealT> > xr_rcp = Teuchos::rcp( new std::vector<RealT>(nx+2,0.0) );
    ROL::StdVector<RealT> xr(xr_rcp);
    Teuchos::RCP<std::vector<RealT> > d_rcp  = Teuchos::rcp( new std::vector<RealT>(nx+2,0.0) );
    //ROL::StdVector<RealT> d(d_rcp);
      Teuchos::RCP<ROL::StdVector<RealT> > d = Teuchos::rcp(new ROL::StdVector<RealT>(d_rcp));
    for ( int i = 0; i < nx+2; i++ ) {
      (*xr_rcp)[i] = random<RealT>(comm);
      (*d_rcp)[i]  = random<RealT>(comm);
      (*z_rcp)[i]  = initZ;
    }
    ROL::RiskVector<RealT> zR(z,true), x1R(x1,true), dR(d,true);
    // Build state and adjoint vectors
    Teuchos::RCP<std::vector<RealT> > u_rcp  = Teuchos::rcp( new std::vector<RealT>(nx,1.0) );
    ROL::StdVector<RealT> u(u_rcp);
    Teuchos::RCP<std::vector<RealT> > p_rcp  = Teuchos::rcp( new std::vector<RealT>(nx,0.0) );
    ROL::StdVector<RealT> p(p_rcp);
    Teuchos::RCP<ROL::Vector<RealT> > up = Teuchos::rcp(&u,false);
    Teuchos::RCP<ROL::Vector<RealT> > pp = Teuchos::rcp(&p,false);
    /**********************************************************************************************/
    /************************* CONSTRUCT SOL COMPONENTS *******************************************/
    /**********************************************************************************************/
    // Build samplers
    int dim = 4;
    int nSamp = parlist->sublist("Problem Description").get("Number of Samples", 20);
    std::vector<RealT> tmp(2,0.0); tmp[0] = -1.0; tmp[1] = 1.0;
    std::vector<std::vector<RealT> > bounds(dim,tmp);
    Teuchos::RCP<ROL::BatchManager<RealT> > bman
      = Teuchos::rcp(new ROL::StdTeuchosBatchManager<RealT,int>(comm));
    Teuchos::RCP<ROL::SampleGenerator<RealT> > sampler
      = Teuchos::rcp(new ROL::MonteCarloGenerator<RealT>(nSamp,bounds,bman,false,false,100));
    /**********************************************************************************************/
    /************************* CONSTRUCT OBJECTIVE FUNCTION ***************************************/
    /**********************************************************************************************/
    // Build risk-averse objective function
    RealT alpha = 1.e-3;
    Teuchos::RCP<ROL::ParametrizedObjective_SimOpt<RealT> > pobjSimOpt
      = Teuchos::rcp(new Objective_BurgersControl<RealT>(alpha,nx));
    Teuchos::RCP<ROL::ParametrizedEqualityConstraint_SimOpt<RealT> > pconSimOpt
      = Teuchos::rcp(new EqualityConstraint_BurgersControl<RealT>(nx));
    Teuchos::RCP<ROL::ParametrizedObjective<RealT> > pObj
      = Teuchos::rcp(new ROL::Reduced_ParametrizedObjective_SimOpt<RealT>(pobjSimOpt,pconSimOpt,up,pp));
    //Teuchos::RCP<ROL::Objective<RealT> > obj = Teuchos::rcp(new ROL::RiskNeutralObjective<RealT>(pObj, sampler, true));
    Teuchos::RCP<ROL::Distribution<RealT> > dist = Teuchos::rcp(new ROL::Parabolic<RealT>(-0.5, 0.5));
    Teuchos::RCP<ROL::PlusFunction<RealT> > pfunc = Teuchos::rcp(new ROL::PlusFunction<RealT>(dist, pfuncSmoothing));
    Teuchos::RCP<ROL::RiskMeasure<RealT> > rmeas = Teuchos::rcp(new ROL::CVaR<RealT>(cvarLevel, 1.0, pfunc));
    Teuchos::RCP<ROL::Objective<RealT> > obj = Teuchos::rcp(new ROL::RiskAverseObjective<RealT>(pObj, rmeas, sampler));
    // Test parametrized objective functions
    *outStream << "Check Derivatives of Parametrized Objective Function\n";
    //x1.set(xr);
      x1->set(xr);
    pObj->setParameter(sampler->getMyPoint(0));
    //pObj->checkGradient(x1,d,true,*outStream);
      pObj->checkGradient(*x1,*d,true,*outStream);
    //pObj->checkHessVec(x1,d,true,*outStream);
      pObj->checkHessVec(*x1,*d,true,*outStream);
    //obj->checkGradient(x1,d,true,*outStream);
      obj->checkGradient(x1R,dR,true,*outStream);
    //obj->checkHessVec(x1,d,true,*outStream);
      obj->checkHessVec(x1R,dR,true,*outStream);
    ROL::Algorithm<RealT> algors("Trust Region", *parlist);
    //algors.run(z, *obj, true, *outStream);
    algors.run(zR, *obj, true, *outStream);
    /**********************************************************************************************/
    /****************** CONSTRUCT SIMULATED CONSTRAINT AND VECTORS ********************************/
    /**********************************************************************************************/

    // Construct SimulatedEqualityConstraint.
    int useW = parlist->sublist("Problem Description").get("Use Constraint Weights", true);
    ROL::SimulatedEqualityConstraint<RealT> simcon(sampler, pconSimOpt, useW);
    // Construct SimulatedObjective.
    ROL::SimulatedObjectiveCVaR<RealT> simobj(sampler, pobjSimOpt, pfunc, cvarLevel);
    // Simulated vectors.
    std::vector<Teuchos::RCP<ROL::Vector<RealT> > > xu_rcp;
    std::vector<Teuchos::RCP<ROL::Vector<RealT> > > vu_rcp;
    int nvecloc = sampler->numMySamples();
    RealT right = 1, left = 0;
    for( int k=0; k<nvecloc; ++k ) {
      Teuchos::RCP<std::vector<RealT> > xuk_rcp = Teuchos::rcp( new std::vector<RealT>(nx,1.0) );
      Teuchos::RCP<std::vector<RealT> > vuk_rcp = Teuchos::rcp( new std::vector<RealT>(nx,1.0) );
      Teuchos::RCP<ROL::Vector<RealT> > xuk = Teuchos::rcp( new ROL::StdVector<RealT>( xuk_rcp ) );
      Teuchos::RCP<ROL::Vector<RealT> > vuk = Teuchos::rcp( new ROL::StdVector<RealT>( vuk_rcp ) );
      for( int i=0; i<nx; ++i ) {
        (*xuk_rcp)[i] = ( (RealT)rand() / (RealT)RAND_MAX ) * (right - left) + left;
        (*vuk_rcp)[i] = ( (RealT)rand() / (RealT)RAND_MAX ) * (right - left) + left;
      }
      xu_rcp.push_back(xuk);
      vu_rcp.push_back(vuk);
    }
    Teuchos::RCP<ROL::SimulatedVector<RealT> > xu = Teuchos::rcp(new ROL::SimulatedVector<RealT>(xu_rcp, bman));
    Teuchos::RCP<ROL::SimulatedVector<RealT> > vu = Teuchos::rcp(new ROL::SimulatedVector<RealT>(vu_rcp, bman));
    // SimOpt vectors.
    Teuchos::RCP<std::vector<RealT> > zvec_rcp = Teuchos::rcp(new std::vector<RealT>(nx+2,0.0));
    Teuchos::RCP<ROL::StdVector<RealT> > zvec = Teuchos::rcp(new ROL::StdVector<RealT>(zvec_rcp));
    Teuchos::RCP<std::vector<RealT> > dvec_rcp = Teuchos::rcp(new std::vector<RealT>(nx+2,0.0));
    Teuchos::RCP<ROL::StdVector<RealT> > dvec = Teuchos::rcp(new ROL::StdVector<RealT>(dvec_rcp));
    for ( int i = 0; i < nx+2; i++ ) {
      (*zvec_rcp)[i] = random<RealT>(comm);
      (*dvec_rcp)[i] = random<RealT>(comm);
    }
    Teuchos::RCP<ROL::RiskVector<RealT> > rz = Teuchos::rcp(new ROL::RiskVector<RealT>(zvec, true));
    Teuchos::RCP<ROL::RiskVector<RealT> > rd = Teuchos::rcp(new ROL::RiskVector<RealT>(dvec, true));
    ROL::Vector_SimOpt<RealT> x(xu, rz);
    ROL::Vector_SimOpt<RealT> v(vu, rd);

    *outStream << std::endl << "TESTING SimulatedEqualityConstraint" << std::endl; 
    simcon.checkApplyJacobian(x, v, *vu, true, *outStream);
    simcon.checkAdjointConsistencyJacobian(*vu, v, x, *vu, x, true, *outStream);
    simcon.checkApplyAdjointHessian(x, *vu, v, x, true, *outStream);
    *outStream << std::endl << "TESTING SimulatedObjective" << std::endl;
    RealT tol = 1e-8;
    simobj.value(x, tol);
    simobj.checkGradient(x, v, true, *outStream);
    simobj.checkHessVec(x, v, true, *outStream);

    ROL::Algorithm<RealT> algo("Composite Step", *parlist);
    ROL::Algorithm<RealT> algo2("Composite Step", *parlist);
    ROL::Algorithm<RealT> algo3("Composite Step", *parlist);
    ROL::Algorithm<RealT> algo4("Composite Step", *parlist);
    ROL::Algorithm<RealT> algo5("Composite Step", *parlist);
    vu->zero();
    for ( int i = 0; i < nx+2; i++ ) {
      (*zvec_rcp)[i] = initZ;
    }
    ROL::SimulatedObjectiveCVaR<RealT> simobjExpval(sampler, pobjSimOpt, pfunc, 0.0);
    ROL::SimulatedObjectiveCVaR<RealT> simobjCVaR3(sampler, pobjSimOpt, pfunc, 0.3);
    ROL::SimulatedObjectiveCVaR<RealT> simobjCVaR6(sampler, pobjSimOpt, pfunc, 0.6);
    ROL::SimulatedObjectiveCVaR<RealT> simobjCVaR7(sampler, pobjSimOpt, pfunc, 0.6);
    algo2.run(x, *vu, simobjExpval, simcon, true, *outStream);
    algo3.run(x, *vu, simobjCVaR3, simcon, true, *outStream);
    algo4.run(x, *vu, simobjCVaR6, simcon, true, *outStream);
    algo5.run(x, *vu, simobjCVaR7, simcon, true, *outStream);
    algo.run(x, *vu, simobj, simcon, true, *outStream);

    // Output control to file.
    if (Teuchos::rank<int>(*comm)==0) {
      std::ofstream file;
      file.open("control-fs-cvar.txt");
      for ( int i = 0; i < nx+2; ++i ) {
        file << (*zvec_rcp)[i] << "\n";
      }
      file.close();
    }

    ROL::RiskVector<RealT> &rxfz = Teuchos::dyn_cast<ROL::RiskVector<RealT> >(*(x.get_2()));
    Teuchos::RCP<ROL::Vector<RealT> > rfz = rxfz.getVector();
    ROL::StdVector<RealT> &rfz_std = Teuchos::dyn_cast<ROL::StdVector<RealT> >(*rfz);
    z->set(rfz_std);
    ROL::Algorithm<RealT> algors2("Trust Region", *parlist);
    algors2.run(zR, *obj, true, *outStream);

  }
  catch (std::logic_error err) {
    *outStream << err.what() << "\n";
    errorFlag = -1000;
  }; // end try

  if (errorFlag != 0)
    std::cout << "End Result: TEST FAILED\n";
  else
    std::cout << "End Result: TEST PASSED\n";

  return 0;
}