IPOPTSolverLean.cc 15.8 KB
Newer Older
1
2
3
4
5
6
7
8
9
10
//=============================================================================
//
//  CLASS IPOPTSolverLean - IMPLEMENTATION
//
//=============================================================================

//== INCLUDES =================================================================

//== COMPILE-TIME PACKAGE REQUIREMENTS ========================================
#include <CoMISo/Config/config.hh>
11
#if COMISO_IPOPT_AVAILABLE
12
13
14
15
16
17
//=============================================================================


#include "IPOPTSolverLean.hh"
#include "NProblemGmmInterface.hh"
#include "NProblemInterface.hh"
18
#include "NProblemIPOPT.hh"
19
20
21
22
#include "NConstraintInterface.hh"
#include "BoundConstraint.hh"
#include "CoMISo/Utils/CoMISoError.hh"

23
#include <Base/Debug/DebConfig.hh>
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
#include <Base/Debug/DebTime.hh>

#include <gmm/gmm.h>

#include <IpTNLP.hpp>
#include <IpIpoptApplication.hpp>
#include <IpSolveStatistics.hpp>

//== NAMESPACES ===============================================================

namespace COMISO {

//== IMPLEMENTATION ========================================================== 


// smart pointer to IpoptApplication to set options etc.
class IPOPTSolverLean::Impl 
{// Create an instance of the IpoptApplication
public:
  Impl() : app_(IpoptApplicationFactory()) {}

public:
  Ipopt::SmartPtr<Ipopt::IpoptApplication> app_;
};

// Constructor
IPOPTSolverLean::IPOPTSolverLean()
  : impl_(new Impl)
{

54
  // Switch to HSL if available
55
56
57
58
59
60
#if COMISO_HSL_AVAILABLE
  impl_->app_->Options()->SetStringValue("linear_solver", "ma57");
#else
  impl_->app_->Options()->SetStringValue("linear_solver", "mumps");
#endif

61
62
#ifdef DEB_ON
  if (!Debug::Config::query().console())
63
#endif
64
  {// Block any output on cout and cerr from Ipopt.
65
66
    impl_->app_->Options()->SetStringValue("suppress_all_output", "yes");
  }
67

68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
#ifdef WIN32
  // Restrict memory to be able to run larger problems on windows
  // with the default mumps solver
  // TODO: find out what this does and whether it makes sense to do it
  impl_->app_->Options()->SetIntegerValue("mumps_mem_percent", 5);
#endif

  // set default parameters
  impl_->app_->Options()->SetIntegerValue("max_iter", 100);
  //  app->Options()->SetStringValue("derivative_test", "second-order");
  //  app->Options()->SetIntegerValue("print_level", 0);
  //  app->Options()->SetStringValue("expect_infeasible_problem", "yes");
}

IPOPTSolverLean::~IPOPTSolverLean()
{ delete impl_; }

double IPOPTSolverLean::energy()
{
  return impl_->app_->Statistics()->FinalObjective();
}

//-----------------------------------------------------------------------------


static void throw_ipopt_solve_failure(Ipopt::ApplicationReturnStatus const status)
{
  DEB_enter_func
  DEB_warning(1, " IPOPT solve failure code is " << status)
  // TODO: we could translate these return codes, but will not do it for now
  //  enum ApplicationReturnStatus
  //    {
  //      Solve_Succeeded=0,
  //      Solved_To_Acceptable_Level=1,
  //      Infeasible_Problem_Detected=2,
  //      Search_Direction_Becomes_Too_Small=3,
  //      Diverging_Iterates=4,
  //      User_Requested_Stop=5,
  //      Feasible_Point_Found=6,
  //
  //      Maximum_Iterations_Exceeded=-1,
  //      Restoration_Failed=-2,
  //      Error_In_Step_Computation=-3,
  //      Maximum_CpuTime_Exceeded=-4,
  //      Not_Enough_Degrees_Of_Freedom=-10,
  //      Invalid_Problem_Definition=-11,
  //      Invalid_Option=-12,
  //      Invalid_Number_Detected=-13,
  //
  //      Unrecoverable_Exception=-100,
  //      NonIpopt_Exception_Thrown=-101,
  //      Insufficient_Memory=-102,
  //      Internal_Error=-199
  //    };
  //------------------------------------------------------
  switch(status) {
124
  case Ipopt::Maximum_Iterations_Exceeded:
125
126
127
128
129
130
    COMISO_THROW(IPOPT_MAXIMUM_ITERATIONS_EXCEEDED);
  default:
    COMISO_THROW(IPOPT_OPTIMIZATION_FAILED);
  } // endswicth
}

131
132
133
134
135
136
137
static void check_ipopt_status(Ipopt::ApplicationReturnStatus const _stat)
{
  if (_stat != Ipopt::Solve_Succeeded && _stat != Ipopt::Solved_To_Acceptable_Level)
    throw_ipopt_solve_failure(_stat);
}


138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
void IPOPTSolverLean::solve(NProblemInterface* _problem, 
  const std::vector<NConstraintInterface*>& _constraints)
{
  DEB_time_func_def;
  //----------------------------------------------------------------------------
  // 1. Create an instance of IPOPT NLP
  //----------------------------------------------------------------------------
  Ipopt::SmartPtr<Ipopt::TNLP> np = new NProblemIPOPT(_problem, _constraints);
  NProblemIPOPT* np2 = dynamic_cast<NProblemIPOPT*> (Ipopt::GetRawPtr(np));

  //----------------------------------------------------------------------------
  // 2. exploit special characteristics of problem
  //----------------------------------------------------------------------------

  DEB_out(2,"exploit detected special properties: ");
  if(np2->hessian_constant())
  {
    DEB_out(2,"*constant hessian* ");
    impl_->app_->Options()->SetStringValue("hessian_constant", "yes");
  }

  if(np2->jac_c_constant())
  {
    DEB_out(2, "*constant jacobian of equality constraints* ");
    impl_->app_->Options()->SetStringValue("jac_c_constant", "yes");
  }

  if(np2->jac_d_constant())
  {
    DEB_out(2, "*constant jacobian of in-equality constraints*");
    impl_->app_->Options()->SetStringValue("jac_d_constant", "yes");
  }
  DEB_out(2,"\n");

  //----------------------------------------------------------------------------
  // 3. solve problem
  //----------------------------------------------------------------------------

  // Initialize the IpoptApplication and process the options
  Ipopt::ApplicationReturnStatus status = impl_->app_->Initialize();
  if (status != Ipopt::Solve_Succeeded) 
    COMISO_THROW(IPOPT_INITIALIZATION_FAILED);

  status = impl_->app_->OptimizeTNLP( np);

  //----------------------------------------------------------------------------
  // 4. output statistics
  //----------------------------------------------------------------------------
186
  check_ipopt_status(status);
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
  
  // Retrieve some statistics about the solve
  Ipopt::Index iter_count = impl_->app_->Statistics()->IterationCount();
  DEB_out(1,"\n*** IPOPT: The problem solved in " 
    << iter_count << " iterations!\n");

  Ipopt::Number final_obj = impl_->app_->Statistics()->FinalObjective();
  DEB_out(1,"\n*** IPOPT: The final value of the objective function is "
    << final_obj << "\n");
}


//-----------------------------------------------------------------------------


void IPOPTSolverLean::solve(
      NProblemInterface*                        _problem,
      const std::vector<NConstraintInterface*>& _constraints,
      const std::vector<NConstraintInterface*>& _lazy_constraints,
      const double                              _almost_infeasible,
      const int                                 _max_passes        )
{
  DEB_time_func_def;
  //----------------------------------------------------------------------------
  // 0. Initialize IPOPT Application
  //----------------------------------------------------------------------------

  // Initialize the IpoptApplication and process the options
  Ipopt::ApplicationReturnStatus status;
  status = impl_->app_->Initialize();
  if (status != Ipopt::Solve_Succeeded)
    COMISO_THROW(IPOPT_INITIALIZATION_FAILED);

  bool feasible_point_found = false;
  int  cur_pass = 0;
  double acceptable_tolerance = 0.01; // hack: read out from ipopt!!!
  // copy default constraints
  std::vector<NConstraintInterface*> constraints = _constraints;
  std::vector<bool> lazy_added(_lazy_constraints.size(),false);

  // cache statistics of all iterations
  std::vector<int> n_inf;
  std::vector<int> n_almost_inf;

  while(!feasible_point_found && cur_pass <(_max_passes-1))
  {
    ++cur_pass;
    //----------------------------------------------------------------------------
    // 1. Create an instance of current IPOPT NLP
    //----------------------------------------------------------------------------
    Ipopt::SmartPtr<Ipopt::TNLP> np = new NProblemIPOPT(_problem, constraints);
    NProblemIPOPT* np2 = dynamic_cast<NProblemIPOPT*> (Ipopt::GetRawPtr(np));
    // enable caching of solution
    np2->store_solution() = true;

    //----------------------------------------------------------------------------
    // 2. exploit special characteristics of problem
    //----------------------------------------------------------------------------

    DEB_out(2, "detected special properties which will be exploit: ");
    if(np2->hessian_constant())
    {
      DEB_out(2, "*constant hessian* ");
      impl_->app_->Options()->SetStringValue("hessian_constant", "yes");
    }

    if(np2->jac_c_constant())
    {
      DEB_out(2, "*constant jacobian of equality constraints* ");
      impl_->app_->Options()->SetStringValue("jac_c_constant", "yes");
    }

    if(np2->jac_d_constant())
    {
      DEB_out(2, "*constant jacobian of in-equality constraints*");
      impl_->app_->Options()->SetStringValue("jac_d_constant", "yes");
    }
    DEB_out(2, "\n");

    //----------------------------------------------------------------------------
    // 3. solve problem
    //----------------------------------------------------------------------------
    status = impl_->app_->OptimizeTNLP( np);

271
272
    check_ipopt_status(status);

273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
    // check lazy constraints
    n_inf.push_back(0);
    n_almost_inf.push_back(0);
    feasible_point_found = true;
    for(unsigned int i=0; i<_lazy_constraints.size(); ++i)
      if(!lazy_added[i])
      {
        NConstraintInterface* lc = _lazy_constraints[i];

        double v = lc->eval_constraint(&(np2->solution()[0]));

        bool inf        = false;
        bool almost_inf = false;

        if(lc->constraint_type() == NConstraintInterface::NC_EQUAL)
        {
          v = std::abs(v);
          if(v>acceptable_tolerance)
            inf = true;
          else
            if(v>_almost_infeasible)
              almost_inf = true;
        }
        else
          if(lc->constraint_type() == NConstraintInterface::NC_GREATER_EQUAL)
          {
            if(v<-acceptable_tolerance)
              inf = true;
            else
              if(v<_almost_infeasible)
                almost_inf = true;
          }
          else
            if(lc->constraint_type() == NConstraintInterface::NC_LESS_EQUAL)
            {
              if(v>acceptable_tolerance)
                inf = true;
              else
                if(v>-_almost_infeasible)
                  almost_inf = true;
            }

        // infeasible?
        if(inf)
        {
          constraints.push_back(lc);
          lazy_added[i] = true;
          feasible_point_found = false;
          ++n_inf.back();
        }

        // almost violated or violated? -> add to constraints
        if(almost_inf)
        {
          constraints.push_back(lc);
          lazy_added[i] = true;
          ++n_almost_inf.back();
        }
      }
  }

  // no termination after max number of passes?
  if(!feasible_point_found)
  {
    ++cur_pass;

    DEB_warning(2, "*************** could not find feasible point after "
340
      << _max_passes-1 << " -> solving with all lazy constraints...");
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
    for(unsigned int i=0; i<_lazy_constraints.size(); ++i)
      if(!lazy_added[i])
        constraints.push_back(_lazy_constraints[i]);

    //----------------------------------------------------------------------------
    // 1. Create an instance of current IPOPT NLP
    //----------------------------------------------------------------------------
    Ipopt::SmartPtr<Ipopt::TNLP> np = new NProblemIPOPT(_problem, constraints);
    NProblemIPOPT* np2 = dynamic_cast<NProblemIPOPT*> (Ipopt::GetRawPtr(np));
    // enable caching of solution
    np2->store_solution() = true;

    //----------------------------------------------------------------------------
    // 2. exploit special characteristics of problem
    //----------------------------------------------------------------------------

    DEB_out(2, "exploit detected special properties: ");
    if(np2->hessian_constant())
    {
      DEB_out(2, "*constant hessian* ");
      impl_->app_->Options()->SetStringValue("hessian_constant", "yes");
    }

    if(np2->jac_c_constant())
    {
      DEB_out(2, "*constant jacobian of equality constraints* ");
      impl_->app_->Options()->SetStringValue("jac_c_constant", "yes");
    }

    if(np2->jac_d_constant())
    {
      DEB_out(2, "*constant jacobian of in-equality constraints*");
      impl_->app_->Options()->SetStringValue("jac_d_constant", "yes");
    }
    std::cerr << std::endl;

    //----------------------------------------------------------------------------
    // 3. solve problem
    //----------------------------------------------------------------------------
    status = impl_->app_->OptimizeTNLP( np);
  }

  //----------------------------------------------------------------------------
  // 4. output statistics
  //----------------------------------------------------------------------------
386
  check_ipopt_status(status);
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444

  // Retrieve some statistics about the solve
  Ipopt::Index iter_count = impl_->app_->Statistics()->IterationCount();
  DEB_out(1, "\n*** IPOPT: The problem solved in " 
    << iter_count << " iterations!\n");

  Ipopt::Number final_obj = impl_->app_->Statistics()->FinalObjective();
  DEB_out(1, "\n*** IPOPT: The final value of the objective function is "
    << final_obj << "\n");

  DEB_out(2, "############# IPOPT with lazy constraints statistics ###############\n");
  DEB_out(2, "#passes     : " << cur_pass << "( of " << _max_passes << ")\n");
  for(unsigned int i=0; i<n_inf.size(); ++i)
    DEB_out(3, "pass " << i << " induced " << n_inf[i] 
      << " infeasible and " << n_almost_inf[i] << " almost infeasible\n")
}


//-----------------------------------------------------------------------------


void IPOPTSolverLean::solve(NProblemInterface*    _problem)
{
  std::vector<NConstraintInterface*> constraints;
  solve(_problem, constraints);
}


//-----------------------------------------------------------------------------


void IPOPTSolverLean::solve(NProblemGmmInterface* _problem, std::vector<NConstraintInterface*>& _constraints)
{
  DEB_enter_func;
  DEB_warning(1,"******NProblemGmmInterface is deprecated!!! -> use NProblemInterface *******");

  //----------------------------------------------------------------------------
  // 1. Create an instance of IPOPT NLP
  //----------------------------------------------------------------------------
  Ipopt::SmartPtr<Ipopt::TNLP> np = new NProblemGmmIPOPT(_problem, _constraints);

  //----------------------------------------------------------------------------
  // 2. solve problem
  //----------------------------------------------------------------------------

  // Initialize the IpoptApplication and process the options
  Ipopt::ApplicationReturnStatus status = impl_->app_->Initialize();
  if (status != Ipopt::Solve_Succeeded)
     COMISO_THROW(IPOPT_INITIALIZATION_FAILED);

  //----------------------------------------------------------------------------
  // 3. solve problem
  //----------------------------------------------------------------------------
  status = impl_->app_->OptimizeTNLP(np);

  //----------------------------------------------------------------------------
  // 4. output statistics
  //----------------------------------------------------------------------------
445
  check_ipopt_status(status);
446
447
448
449
450
451
452
453
454
455
456
457
458
459

  // Retrieve some statistics about the solve
  Ipopt::Index iter_count = impl_->app_->Statistics()->IterationCount();
  DEB_out(1,"\n*** IPOPT: The problem solved in " << iter_count << " iterations!\n");

  Ipopt::Number final_obj = impl_->app_->Statistics()->FinalObjective();
  DEB_out(1, "\n*** IPOPT: The final value of the objective function is "
    << final_obj << "\n");
}


//=============================================================================
} // namespace COMISO
//=============================================================================
460
#endif // COMISO_IPOPT_AVAILABLE
461
//=============================================================================