ROL
step/test_08.cpp
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44 
49 #include "Teuchos_GlobalMPISession.hpp"
50 
51 #include "ROL_HS29.hpp"
52 #include "ROL_Algorithm.hpp"
53 
54 typedef double RealT;
55 
56 int main(int argc, char *argv[]) {
57 
58 
59 
60 
61  typedef std::vector<RealT> vec;
62  typedef ROL::StdVector<RealT> SV;
63  typedef ROL::Ptr<ROL::Vector<RealT> > ROL::PtrV;
64 
65  Teuchos::GlobalMPISession mpiSession(&argc, &argv);
66 
67  int iprint = argc - 1;
68  ROL::Ptr<std::ostream> outStream;
69  ROL::nullstream bhs; // outputs nothing
70  if (iprint > 0)
71  outStream = ROL::makePtrFromRef(std::cout);
72  else
73  outStream = ROL::makePtrFromRef(bhs);
74 
75  int errorFlag = 0;
76 
77  try {
78 
79  int xopt_dim = 3; // Dimension of optimization vectors
80  int ci_dim = 1; // Dimension of inequality constraint
81 
82  ROL::Ptr<vec> xopt_ptr = ROL::makePtr<vec>(xopt_dim,1.0); // Feasible initial guess
83 
84  ROL::Ptr<vec> li_ptr = ROL::makePtr<vec>(ci_dim,0.0);
85 
86  ROL::PtrV xopt = ROL::makePtr<SV>(xopt_ptr);
87  ROL::PtrV li = ROL::makePtr<SV>(li_ptr);
88 
89  // Original obective
92 
93  ROL::Ptr<ROL::Objective<RealT> > obj_hs29 = ROL::makePtr<Objective_HS29<RealT>>();
94  ROL::Ptr<ROL::InequalityConstraint<RealT> > incon_hs29 = ROL::makePtr<InequalityConstraint_HS29<RealT>>();
95 
96 
97  std::string stepname = "Interior Point";
98 
99  RealT mu = 0.1; // Initial penalty parameter
100  RealT factor = 0.1; // Penalty reduction factor
101 
102  // Set solver parameters
103  parlist->sublist("General").set("Print Verbosity",1);
104 
105  parlist->sublist("Step").sublist("Interior Point").set("Initial Barrier Penalty",mu);
106  parlist->sublist("Step").sublist("Interior Point").set("Minimium Barrier Penalty",1e-8);
107  parlist->sublist("Step").sublist("Interior Point").set("Barrier Penalty Reduction Factor",factor);
108  parlist->sublist("Step").sublist("Interior Point").set("Subproblem Iteration Limit",30);
109 
110  parlist->sublist("Step").sublist("Composite Step").sublist("Optimality System Solver").set("Nominal Relative Tolerance",1.e-4);
111  parlist->sublist("Step").sublist("Composite Step").sublist("Optimality System Solver").set("Fix Tolerance",true);
112  parlist->sublist("Step").sublist("Composite Step").sublist("Tangential Subproblem Solver").set("Iteration Limit",20);
113  parlist->sublist("Step").sublist("Composite Step").sublist("Tangential Subproblem Solver").set("Relative Tolerance",1e-2);
114  parlist->sublist("Step").sublist("Composite Step").set("Output Level",0);
115 
116  parlist->sublist("Status Test").set("Gradient Tolerance",1.e-12);
117  parlist->sublist("Status Test").set("Constraint Tolerance",1.e-8);
118  parlist->sublist("Status Test").set("Step Tolerance",1.e-8);
119  parlist->sublist("Status Test").set("Iteration Limit",100);
120 
121  ROL::OptimizationProblem<RealT> problem( obj_hs29, xopt, incon_hs29, li, parlist);
122 
123  // Define algorithm.
124  ROL::Ptr<ROL::Algorithm<RealT> > algo;
125  algo = ROL::makePtr<ROL::Algorithm<RealT>>(stepname,*parlist);
126 
127  algo->run(problem,true,*outStream);
128 
129 
130 
131  *outStream << std::endl << std::setw(20) << "Computed Minimizer" << std::endl;
132  for( int i=0;i<xopt_dim;++i ) {
133  *outStream << std::setw(20) << (*xopt_ptr)[i] << std::endl;
134  }
135 
136  *outStream << "Exact minimizers: x* = (a,b,c), (a,-b,-c), (-a,b,-c), (-a,-b,c)" << std::endl;
137  *outStream << "Where a=4, b=" << 2*std::sqrt(2) << ", and c=2" << std::endl;
138 
139  }
140  catch (std::logic_error& err) {
141  *outStream << err.what() << "\n";
142  errorFlag = -1000;
143  }; // end try
144 
145  if (errorFlag != 0)
146  std::cout << "End Result: TEST FAILED\n";
147  else
148  std::cout << "End Result: TEST PASSED\n";
149 
150  return 0;
151 
152 
153 
154 }
Contains definitions for W. Hock and K. Schittkowski 32nd test problem which contains only inequality...
Provides the ROL::Vector interface for scalar values, to be used, for example, with scalar constraint...
basic_nullstream< char, char_traits< char >> nullstream
Definition: ROL_Stream.hpp:72
int main(int argc, char *argv[])