int main(int argc, char* argv[])
{
EnvPtr env = (EnvPtr) new Environment();
OptionDBPtr options;
MINOTAUR_AMPL::AMPLInterfacePtr iface = MINOTAUR_AMPL::AMPLInterfacePtr();
ProblemPtr inst;
SolutionPtr sol, sol2;
double obj_sense =1.0;
// jacobian is read from AMPL interface and passed on to branch-and-bound
JacobianPtr jPtr;
// hessian is read from AMPL interface and passed on to branch-and-bound
MINOTAUR_AMPL::AMPLHessianPtr hPtr;
// the branch-and-bound
BranchAndBound *bab = 0;
PresolverPtr pres;
EngineFactory *efac;
const std::string me("qg: ");
BrancherPtr br = BrancherPtr(); // NULL
PCBProcessorPtr nproc;
NodeIncRelaxerPtr nr;
//handlers
HandlerVector handlers;
IntVarHandlerPtr vHand;
LinearHandlerPtr lHand;
QGAdvHandlerPtr qgHand;
RCHandlerPtr rcHand;
//engines
EnginePtr nlp_e;
EnginePtr proj_nlp_e;
EnginePtr l1proj_nlp_e;
LPEnginePtr lin_e; // lp engine
LoggerPtr logger_ = (LoggerPtr) new Logger(LogInfo);
VarVector *orig_v=0;
int err = 0;
// start timing.
env->startTimer(err);
if (err) {
goto CLEANUP;
}
setInitialOptions(env);
iface = (MINOTAUR_AMPL::AMPLInterfacePtr)
new MINOTAUR_AMPL::AMPLInterface(env, "qg");
// parse options
env->readOptions(argc, argv);
options = env->getOptions();
options->findString("interface_type")->setValue("AMPL");
if (0!=showInfo(env)) {
goto CLEANUP;
}
loadProblem(env, iface, inst, &obj_sense);
// Initialize engines
nlp_e = getNLPEngine(env, inst); //Engine for Original problem
efac = new EngineFactory(env);
lin_e = efac->getLPEngine(); // lp engine
delete efac;
// get presolver.
orig_v = new VarVector(inst->varsBegin(), inst->varsEnd());
pres = presolve(env, inst, iface->getNumDefs(), handlers);
handlers.clear();
if (Finished != pres->getStatus() && NotStarted != pres->getStatus()) {
env->getLogger()->msgStream(LogInfo) << me
<< "status of presolve: "
<< getSolveStatusString(pres->getStatus()) << std::endl;
writeSol(env, orig_v, pres, SolutionPtr(), pres->getStatus(), iface);
writeBnbStatus(env, bab, obj_sense);
goto CLEANUP;
}
if (options->findBool("solve")->getValue()==true) {
if (true==options->findBool("use_native_cgraph")->getValue()) {
inst->setNativeDer();
}
// Initialize the handlers for branch-and-cut
lHand = (LinearHandlerPtr) new LinearHandler(env, inst);
lHand->setModFlags(false, true);
handlers.push_back(lHand);
assert(lHand);
vHand = (IntVarHandlerPtr) new IntVarHandler(env, inst);
vHand->setModFlags(false, true);
handlers.push_back(vHand);
assert(vHand);
// Use of perspective handler is user choice
if (env->getOptions()->findBool("perspective")->getValue() == true) {
PerspCutHandlerPtr pcHand = (PerspCutHandlerPtr) new
PerspCutHandler(env, inst);
pcHand->findPRCons();
if (pcHand->getStatus()) {
qgHand = (QGAdvHandlerPtr) new QGAdvHandler(env, inst, nlp_e, pcHand);
} else {
qgHand = (QGAdvHandlerPtr) new QGAdvHandler(env, inst, nlp_e);
}
} else {
qgHand = (QGAdvHandlerPtr) new QGAdvHandler(env, inst, nlp_e);
}
qgHand->setModFlags(false, true);
handlers.push_back(qgHand);
assert(qgHand);
if (options->findBool("rc_fix")->getValue()) {
rcHand = (RCHandlerPtr) new RCHandler(env);
rcHand->setModFlags(false, true);
handlers.push_back(rcHand);
assert(rcHand);
}
// report name
env->getLogger()->msgStream(LogExtraInfo) << me << "handlers used:"
<< std::endl;
for (HandlerIterator h = handlers.begin(); h != handlers.end(); ++h) {
env->getLogger()->msgStream(LogExtraInfo) << me << (*h)->getName()
<< std::endl;
}
// Only store bound-changes of relaxation (not problem)
nr = (NodeIncRelaxerPtr) new NodeIncRelaxer(env, handlers);
nr->setModFlag(false);
nr->setEngine(lin_e);
nproc = (PCBProcessorPtr) new PCBProcessor(env, lin_e, handlers);
if (env->getOptions()->findString("brancher")->getValue() == "rel") {
ReliabilityBrancherPtr rel_br =
(ReliabilityBrancherPtr) new ReliabilityBrancher(env, handlers);
rel_br->setEngine(lin_e);
nproc->setBrancher(rel_br);
br = rel_br;
} else if (env->getOptions()->findString("brancher")->getValue()
== "maxvio") {
MaxVioBrancherPtr mbr = (MaxVioBrancherPtr)
new MaxVioBrancher(env, handlers);
nproc->setBrancher(mbr);
br = mbr;
} else if (env->getOptions()->findString("brancher")->getValue()
== "lex") {
LexicoBrancherPtr lbr = (LexicoBrancherPtr)
new LexicoBrancher(env, handlers);
br = lbr;
}
nproc->setBrancher(br);
env->getLogger()->msgStream(LogExtraInfo) << me <<
"brancher used = " << br->getName() << std::endl;
bab = new BranchAndBound(env, inst);
bab->setNodeRelaxer(nr);
bab->setNodeProcessor(nproc);
bab->shouldCreateRoot(true);
// start solving
bab->solve();
bab->writeStats(env->getLogger()->msgStream(LogExtraInfo));
//bab->writeStats(std::cout);
nlp_e->writeStats(env->getLogger()->msgStream(LogExtraInfo));
lin_e->writeStats(env->getLogger()->msgStream(LogExtraInfo));
for (HandlerVector::iterator it=handlers.begin(); it!=handlers.end();
++it) {
//(*it)->writeStats(std::cout);
(*it)->writeStats(env->getLogger()->msgStream(LogExtraInfo));
}
writeSol(env, orig_v, pres, bab->getSolution(), bab->getStatus(), iface);
writeBnbStatus(env, bab, obj_sense);
}
CLEANUP:
if (iface) {
delete iface;
}
if (orig_v) {
delete orig_v;
}
if (bab) {
delete bab;
}
return 0;
}
//! main routine implementing outer approximation
int main(int argc, char** argv)
{
//! Declaration of Variables ============================================
//! interface to AMPL (NULL):
MINOTAUR_AMPL::AMPLInterfacePtr iface = MINOTAUR_AMPL::AMPLInterfacePtr();
MINOTAUR_AMPL::JacobianPtr jPtr; //! Jacobian read from AMPL
MINOTAUR_AMPL::HessianOfLagPtr hPtr; //! Hessian read from AMPL
//! environment, timers, options:
EnvPtr env = (EnvPtr) new Environment();
TimerFactory *tFactory = new TimerFactory();
Timer *timer=tFactory->getTimer();
OptionDBPtr options; //! AMPL and MINOTAUR options
//! problem pointers (MINLP, NLP, MILP):
ProblemPtr minlp; //! MINLP instance to be solved
ProblemPtr milp; //! MILP master problem
//! solver pointers, including status
FilterSQPEngine e(env); //! NLP engine: FilterSQP
EngineStatus status;
//! pointers to manipulate variables & constraints
VariablePtr v, objVar; //! variable pointer (objective)
ObjectivePtr objFun; //! remember objective function pt.
//! local variables
Double *x, *xsoln;
Double *lobnd, *upbnd;
Double objfLo = -INFINITY, objfUp = INFINITY, objfNLP, objfMIP;
Double tol = 1E-2;
Int feasibleNLP = 0, iterOA = 1, n;
// ======================================================================
//! start the timer
timer->start();
//! make sure solver is used correctly
if (argc < 2) {
usage();
return -1;
}
//! add AMPL options & flags to environment: flags (options without values)
options = env->getOptions();
add_ampl_flags(options);
env->readOptions(argc, argv); //! parse options
if (!checkUserOK(options,env)) goto CLEANUP; //! check if user needs help
//! read MINLP from AMPL & create Hessian/Jacobian for NLP solves
iface = (MINOTAUR_AMPL::AMPLInterfacePtr) new MINOTAUR_AMPL::AMPLInterface(env);
minlp = iface->readInstance(options->findString("problem_file")->getValue(),false);
jPtr = (MINOTAUR_AMPL::JacobianPtr) new MINOTAUR_AMPL::Jacobian(iface);
hPtr = (MINOTAUR_AMPL::HessianOfLagPtr) new MINOTAUR_AMPL::HessianOfLag(iface);
minlp->setJacobian(jPtr);
minlp->setHessian(hPtr);
//! Display number of constraints and variables, and MINLP problem
minlp->calculateSize();
n = minlp->getNumVars();
std::cout << "No. of vars, cons = " << minlp->getNumVars()
<< minlp->getNumCons() << std::endl;
std::cout << std::endl << "The MINLP problem is: " << std::endl;
minlp->write(std::cout);
//! load the MINLP into the NLP solver (FilterSQP)
e.load(minlp);
//! get initial point & save original bounds
x = new Double[n];
xsoln = new Double[n];
lobnd = new Double[n];
upbnd = new Double[n];
std::copy(iface->getInitialPoint(),iface->getInitialPoint()+n,x);
for (VariableConstIterator i=minlp->varsBegin(); i!=minlp->varsEnd(); ++i) {
v = *i;
lobnd[v->getId()] = v->getLb();
upbnd[v->getId()] = v->getUb();
}
//! initialize the MILP master problem by copying variables & linear c/s
milp = (ProblemPtr) new Problem();
objFun = minlp->getObjective();
objVar = VariablePtr();
initMaster(minlp, milp, objVar, objFun, x);
while ((objfLo <= objfUp)&&(iterOA<4)){
std::cout << "Iteration " << iterOA << std::endl
<< "===============" << std::endl << std::endl;
//! set-up and solve NLP(y) with fixed integers
solveNLP(minlp, e, x, objfNLP, feasibleNLP, n);
std::cout << "Solved NLP " << iterOA << " objective = " << objfNLP
<< " NLPfeasible = " << feasibleNLP << std::endl;
if (feasibleNLP && (objfNLP-tol < objfUp)) {
objfUp = objfNLP - tol;
std::copy(x,x+n,xsoln);
}
//! update MILP master problem by adding outer approximations
updateMaster(minlp, milp, objVar, objFun, objfUp, x, n);
//! solve MILP master problem
solveMaster(env, milp, x, &objfMIP, n);
objfLo = objfMIP;
iterOA = iterOA + 1;
} // end while (objfLo <= objfUp)
//! output final result & timing
std::cout << std::endl << "END outer-approximation: f(x) = " << objfUp
<< " time used = " << timer->query() << std::endl;
CLEANUP:
//! free storage
delete timer;
delete tFactory;
if (minlp) {
minlp->clear();
delete [] x;
delete [] xsoln;
delete [] lobnd;
delete [] upbnd;
}
if (milp) {
milp->clear();
}
return 0;
} // end outer approximation main
