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GamsIpopt.cpp
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GamsIpopt.cpp
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// Copyright (C) GAMS Development and others
// All Rights Reserved.
// This code is published under the Eclipse Public License.
//
// Author: Stefan Vigerske
#include "GamsLinksConfig.h"
#include "GamsIpopt.hpp"
#include "GamsNLP.hpp"
#include "GamsJournal.hpp"
#include "IpoptConfig.h"
#include "IpSolveStatistics.hpp"
#include <cstdio>
#include <cstring>
#include <cassert>
#include <climits>
// GAMS
#include "gmomcc.h"
#include "gevmcc.h"
#include "palmcc.h"
#include "GamsLicensing.h"
#include "GamsHelper.h"
#ifdef GAMS_BUILD
#include "GamsHSLInit.h"
#endif
using namespace Ipopt;
void GamsIpopt::setupIpopt()
{
ipopt = new IpoptApplication(false);
// setup own journal
if( gev != NULL )
{
SmartPtr<Journal> jrnl = new GamsJournal(gev, "console", J_ITERSUMMARY);
jrnl->SetPrintLevel(J_DBG, J_NONE);
if( !ipopt->Jnlst()->AddJournal(jrnl) )
gevLogStat(gev, "Failed to register GamsJournal for IPOPT output.");
}
// add options
ipopt->RegOptions()->SetRegisteringCategory("Output");
ipopt->RegOptions()->AddStringOption2("print_eval_error",
"Switch to enable printing information about function evaluation errors into the GAMS listing file.",
"yes",
"no", "", "yes", "");
ipopt->RegOptions()->AddStringOption2("report_mininfeas_solution",
"Switch to report intermediate solution with minimal constraint violation to GAMS if the final solution is not feasible.",
"no",
"no", "", "yes", "",
"This option allows to obtain the most feasible solution found by Ipopt during the iteration process, if it stops at a (locally) infeasible solution, due to a limit (time, iterations, ...), or with a failure in the restoration phase.");
// change some option defaults
ipopt->Options()->clear();
ipopt->Options()->SetNumericValue("bound_relax_factor", 1e-10, true, true);
ipopt->Options()->SetIntegerValue("acceptable_iter", 0, true, true); // GAMS does not have a proper status if Ipopt returns with this
ipopt->Options()->SetNumericValue("constr_viol_tol", 1e-6, true, true); // as with many other GAMS solvers
ipopt->Options()->SetStringValue("mu_strategy", "adaptive", true, true);
ipopt->Options()->SetStringValue("ma86_order", "auto", true, true);
if( ipoptlicensed )
{
ipopt->Options()->SetStringValue("linear_solver", "ma27", true, true);
ipopt->Options()->SetStringValue("linear_system_scaling", "mc19", true, true);
}
else
{
ipopt->Options()->SetStringValue("linear_solver", "mumps", true, true);
}
warmstart = false;
}
int GamsIpopt::readyAPI(
struct gmoRec* gmo_
)
{
struct palRec* pal;
char buffer[GMS_SSSIZE];
gmo = gmo_;
assert(gmo != NULL);
/* free a previous Ipopt instance, if existing */
ipopt = NULL;
gev = (gevRec*)gmoEnvironment(gmo);
assert(gev != NULL);
ipoptlicensed = false;
if( !palCreate(&pal, buffer, sizeof(buffer)) )
{
gevLogStat(gev, buffer);
return 1;
}
#if PALAPIVERSION >= 3
palSetSystemName(pal, "COIN-OR Ipopt");
palGetAuditLine(pal,buffer);
gevLogStat(gev, "");
gevLogStat(gev, buffer);
gevStatAudit(gev, buffer);
#endif
#ifdef GAMS_BUILD
GAMSinitLicensing(gmo, pal);
if( gevGetIntOpt(gev, gevCurSolver) == gevSolver2Id(gev, "ipopth") )
{
ipoptlicensed = GAMScheckIpoptLicense(pal, false);
if( !ipoptlicensed )
{
gmoSolveStatSet(gmo, gmoSolveStat_License);
gmoModelStatSet(gmo, gmoModelStat_LicenseError);
gevLogStatPChar(gev, "\nYou may want to try the free version IPOPT instead of IPOPTH.\n\n");
return 1;
}
GamsHSLInit();
}
#endif
gevLogStatPChar(gev, "\nCOIN-OR Interior Point Optimizer (Ipopt Library " IPOPT_VERSION ")\n");
if( ipoptlicensed )
gevLogStatPChar(gev, "written by A. Waechter, commercially supported by GAMS Development Corp.\n");
else
gevLogStatPChar(gev, "written by A. Waechter.\n");
#ifdef GAMS_BUILD
if( !ipoptlicensed && GAMScheckIpoptLicense(pal, true) )
gevLogPChar(gev, "\nNote: This is the free version IPOPT, but you could also use the commercially supported and potentially higher performance version IPOPTH.\n");
#endif
palFree(&pal);
gmoObjStyleSet(gmo, gmoObjType_Fun);
gmoObjReformSet(gmo, 1);
gmoIndexBaseSet(gmo, 0);
try
{
setupIpopt();
}
catch( const std::exception& e )
{
gevLogStat(gev, e.what());
return 1;
}
gevTerminateInstall(gev);
if( gmoScaleOpt(gmo) )
ipopt->Options()->SetStringValue("nlp_scaling_method", "none", true, true);
// if linear objective, then Ipopt can skip reevaluating the objective gradient
if( gmoObjNLNZ(gmo) == 0 )
ipopt->Options()->SetStringValue("grad_f_constant", "yes", true, true);
if( gmoNLM(gmo) == 0 )
{
// if linear constraints, then Ipopt can skip reevaluating the Jacobian
ipopt->Options()->SetStringValue("jac_c_constant", "yes", true, true);
ipopt->Options()->SetStringValue("jac_d_constant", "yes", true, true);
// if also quadratic objective, then Ipopt can skip reevaluating the Hessian, too
if( gmoModelType(gmo) == gmoProc_qcp || gmoModelType(gmo) == gmoProc_rmiqcp )
ipopt->Options()->SetStringValue("hessian_constant", "yes", true, true);
}
else
{
// there are nonlinear constraints, but lets see if maybe all equalities are linear or all inequalities are linear
bool jac_c_constant = true;
bool jac_d_constant = true;
int nz, qnz, nlnz;
for( int i = 0; i < gmoM(gmo) && (jac_c_constant || jac_d_constant); ++i )
{
gmoGetRowStat(gmo, i, &nz, &qnz, &nlnz);
if( nlnz == 0 )
continue;
if( gmoGetEquTypeOne(gmo, i) == gmoequ_E ) // nonlinear equality
jac_c_constant = false;
else
jac_d_constant = false; // nonlinear inequality or free
}
if( jac_c_constant )
ipopt->Options()->SetStringValue("jac_c_constant", "yes", true, true);
if( jac_d_constant )
ipopt->Options()->SetStringValue("jac_d_constant", "yes", true, true);
}
if( gmoSense(gmo) == gmoObj_Max )
ipopt->Options()->SetNumericValue("obj_scaling_factor", -1.0, true, true);
// read user options, if given
if( gmoOptFile(gmo) > 0 )
{
char buffer[GMS_SSSIZE];
ipopt->Options()->SetStringValue("print_user_options", "yes", true, true);
gmoNameOptFile(gmo, buffer);
ipopt->Initialize(buffer, false);
}
else
ipopt->Initialize("", false);
nlp = new GamsNLP(gmo);
delete[] boundtype;
boundtype = NULL;
// get tolerances
ipopt->Options()->GetNumericValue("diverging_iterates_tol", nlp->div_iter_tol, "");
ipopt->Options()->GetNumericValue("constr_viol_tol", nlp->conviol_tol, "");
ipopt->Options()->GetNumericValue("compl_inf_tol", nlp->compl_tol, "");
// initialize GMO hessian, if required
// TODO if hessian is only approximated by GMO (extr. func without 2nd deriv info), then could suggest user to enable Ipopts hessian approx via log
std::string hess_approx;
ipopt->Options()->GetStringValue("hessian_approximation", hess_approx, "");
if( hess_approx == "exact" )
{
int do2dir = 0;
int dohess = 1;
gmoHessLoad(gmo, 0, &do2dir, &dohess);
if( !dohess )
{
gevLogStat(gev, "Failed to initialize Hessian structure. We continue with a limited-memory Hessian approximation!");
ipopt->Options()->SetStringValue("hessian_approximation", "limited-memory");
}
}
ipopt->Options()->GetBoolValue("report_mininfeas_solution", nlp->reportmininfeas, "");
return 0;
}
int GamsIpopt::callSolver()
{
assert(gmo != NULL);
assert(gev != NULL);
assert(IsValid(ipopt));
assert(IsValid(nlp));
gmoObjStyleSet(gmo, gmoObjType_Fun);
gmoObjReformSet(gmo, 1);
gmoIndexBaseSet(gmo, 0);
#if GMOAPIVERSION >= 22
if( gmoNZ64(gmo) > INT_MAX )
{
gevLogStat(gev, "ERROR: Problems with more than 2^31 nonzeros not supported.");
gmoSolveStatSet(gmo, gmoSolveStat_Capability);
gmoModelStatSet(gmo, gmoModelStat_NoSolutionReturned);
return 0;
}
#endif
// process options and setup NLP
ipopt->Options()->SetIntegerValue("max_iter", gevGetIntOpt(gev, gevIterLim), true, true);
ipopt->Options()->SetNumericValue("max_wall_time", gevGetDblOpt(gev, gevResLim), true, true);
double ipoptinf;
ipopt->Options()->GetNumericValue("nlp_lower_bound_inf", ipoptinf, "");
gmoMinfSet(gmo, ipoptinf);
ipopt->Options()->GetNumericValue("nlp_upper_bound_inf", ipoptinf, "");
gmoPinfSet(gmo, ipoptinf);
bool printevalerror;
ipopt->Options()->GetBoolValue("print_eval_error", printevalerror, "");
gmoEvalErrorMsg(gmo, printevalerror);
if( boundtype == NULL )
{
// remember for which variable a lower or upper bound is given
// we need this in modifyProblem (though we have no way to know whether that will be called, it seems)
boundtype = new uint8_t[gmoN(gmo)];
for( int i = 0; i < gmoN(gmo); ++i )
{
boundtype[i] = 0;
if( gmoGetVarLowerOne(gmo, i) != gmoMinf(gmo) )
boundtype[i] |= 1u;
if( gmoGetVarUpperOne(gmo, i) != gmoPinf(gmo) )
boundtype[i] |= 2u;
}
}
// set number of threads in linear algebra
if( gevGetIntOpt(gev, gevThreadsRaw) != 0 )
GAMSsetNumThreads(gev, gevThreads(gev));
else
GAMSsetNumThreads(gev, 1);
// solve NLP
ApplicationReturnStatus status;
try
{
if( !warmstart )
status = ipopt->OptimizeTNLP(GetRawPtr(nlp));
else
status = ipopt->ReOptimizeTNLP(GetRawPtr(nlp));
}
catch( IpoptException& e )
{
status = Unrecoverable_Exception;
gevLogStat(gev, e.Message().c_str());
}
SmartPtr<SolveStatistics> solvestat = ipopt->Statistics();
if( IsValid(solvestat) )
{
gmoSetHeadnTail(gmo, gmoHresused, solvestat->TotalWallclockTime());
gmoSetHeadnTail(gmo, gmoHiterused, solvestat->IterationCount());
}
// process solution status
switch( status )
{
case Solve_Succeeded:
case Solved_To_Acceptable_Level:
case Infeasible_Problem_Detected:
case Search_Direction_Becomes_Too_Small:
case Diverging_Iterates:
case User_Requested_Stop:
case Maximum_Iterations_Exceeded:
case Maximum_CpuTime_Exceeded:
case Maximum_WallTime_Exceeded:
case Restoration_Failed:
case Error_In_Step_Computation:
case Feasible_Point_Found:
break; // these should have been handled by FinalizeSolution already
case Not_Enough_Degrees_Of_Freedom:
gmoModelStatSet(gmo, gmoModelStat_ErrorNoSolution);
gmoSolveStatSet(gmo, gmoSolveStat_SolverErr);
break;
case Invalid_Problem_Definition:
gmoModelStatSet(gmo, gmoModelStat_ErrorNoSolution);
gmoSolveStatSet(gmo, gmoSolveStat_SetupErr);
break;
case Invalid_Option:
{
gmoModelStatSet(gmo, gmoModelStat_ErrorNoSolution);
gmoSolveStatSet(gmo, gmoSolveStat_SetupErr);
std::string linsolver;
ipopt->Options()->GetStringValue("linear_solver", linsolver, "");
if( linsolver == "pardiso" )
{
gevLogStat(gev, "NOTE: With Ipopt 3.14 (GAMS 36), value pardiso of option linear_solver has been renamed to pardisomkl.");
gevLogStat(gev, " If using Pardiso from MKL was intended, the Ipopt options file needs to be changed to \"linear_solver pardisomkl\".");
}
break;
}
case Invalid_Number_Detected:
gmoModelStatSet(gmo, gmoModelStat_ErrorNoSolution);
gmoSolveStatSet(gmo, gmoSolveStat_EvalError);
break;
case Unrecoverable_Exception:
case Internal_Error:
gmoModelStatSet(gmo, gmoModelStat_ErrorNoSolution);
gmoSolveStatSet(gmo, gmoSolveStat_InternalErr);
break;
case Insufficient_Memory:
gmoModelStatSet(gmo, gmoModelStat_ErrorNoSolution);
gmoSolveStatSet(gmo, gmoSolveStat_SolverErr);
break;
case NonIpopt_Exception_Thrown:
default:
gmoModelStatSet(gmo, gmoModelStat_ErrorNoSolution);
gmoSolveStatSet(gmo, gmoSolveStat_SystemErr);
break;
}
if( gmoModelType(gmo) == gmoProc_cns )
switch( gmoModelStat(gmo) )
{
case gmoModelStat_OptimalGlobal:
case gmoModelStat_OptimalLocal:
case gmoModelStat_Feasible:
case gmoModelStat_Integer:
gmoModelStatSet(gmo, gmoModelStat_Solved);
}
return 0;
}
int GamsIpopt::modifyProblem()
{
assert(IsValid(ipopt));
assert(IsValid(nlp));
gmoObjStyleSet(gmo, gmoObjType_Fun);
gmoObjReformSet(gmo, 1);
gmoIndexBaseSet(gmo, 0);
if( !warmstart )
{
ipopt->Options()->SetStringValue("warm_start_init_point", "yes");
// these could make sense, but lets let the user set these (they usually don't affect the first solve)
// ipopt->Options()->SetNumericValue("warm_start_bound_frac", 1e-16, true, false);
// ipopt->Options()->SetNumericValue("warm_start_bound_push", 1e-16, true, false);
// ipopt->Options()->SetNumericValue("warm_start_mult_bound_push", 1e-16, true, false);
// ipopt->Options()->SetNumericValue("warm_start_slack_bound_frac", 1e-16, true, false);
// ipopt->Options()->SetNumericValue("warm_start_slack_bound_push", 1e-16, true, false);
// ipopt->Options()->SetNumericValue("mu_init", 1e-8, true, false);
warmstart = true;
}
// check whether structure of NLP did not change
// we can assume that nonzero-structure and equation sense (=L=, ...) didn't change
// but for Ipopt it is a structural change if a variable bound appeared or disappeared
bool structurechanged = false;
for( int i = 0; i < gmoN(gmo); ++i )
{
uint8_t newboundtype = 0;
if( gmoGetVarLowerOne(gmo, i) != gmoMinf(gmo) )
newboundtype |= 1u;
if( gmoGetVarUpperOne(gmo, i) != gmoPinf(gmo) )
newboundtype |= 2u;
if( boundtype[i] != newboundtype )
structurechanged = true;
boundtype[i] = newboundtype;
}
ipopt->Options()->SetStringValue("warm_start_same_structure", structurechanged ? "no" : "yes");
return 0;
}
#define GAMSSOLVER_ID ipo
#define GAMSSOLVER_HAVEMODIFYPROBLEM
#include "GamsEntryPoints_tpl.c"
DllExport void STDCALL GAMSSOLVER_CONCAT(GAMSSOLVER_ID,Initialize)(void)
{
gmoInitMutexes();
gevInitMutexes();
palInitMutexes();
}
DllExport void STDCALL GAMSSOLVER_CONCAT(GAMSSOLVER_ID,Finalize)(void)
{
gmoFiniMutexes();
gevFiniMutexes();
palFiniMutexes();
}
DllExport int STDCALL GAMSSOLVER_CONCAT(GAMSSOLVER_ID,Create)(void** Cptr, char* msgBuf, int msgBufLen)
{
assert(Cptr != NULL);
assert(msgBuf != NULL);
*Cptr = NULL;
if( !gmoGetReady(msgBuf, msgBufLen) )
return 1;
if( !gevGetReady(msgBuf, msgBufLen) )
return 1;
if( !palGetReady(msgBuf, msgBufLen) )
return 1;
*Cptr = (void*) new GamsIpopt();
if( *Cptr == NULL )
{
snprintf(msgBuf, msgBufLen, "Out of memory when creating GamsIpopt object.\n");
if( msgBufLen > 0 )
msgBuf[msgBufLen] = '\0';
return 1;
}
return 0;
}
DllExport void STDCALL GAMSSOLVER_CONCAT(GAMSSOLVER_ID,Free)(void** Cptr)
{
assert(Cptr != NULL);
delete (GamsIpopt*)*Cptr;
*Cptr = NULL;
gmoLibraryUnload();
gevLibraryUnload();
palLibraryUnload();
}
DllExport int STDCALL GAMSSOLVER_CONCAT(GAMSSOLVER_ID,CallSolver)(void* Cptr)
{
assert(Cptr != NULL);
return ((GamsIpopt*)Cptr)->callSolver();
}
DllExport int STDCALL GAMSSOLVER_CONCAT(GAMSSOLVER_ID,ReadyAPI)(void* Cptr, gmoHandle_t Gptr)
{
assert(Cptr != NULL);
assert(Gptr != NULL);
return ((GamsIpopt*)Cptr)->readyAPI(Gptr);
}
DllExport int STDCALL GAMSSOLVER_CONCAT(GAMSSOLVER_ID,ModifyProblem)(void* Cptr)
{
assert(Cptr != NULL);
return ((GamsIpopt*)Cptr)->modifyProblem();
}