int main(int argc,char *argv[])
{
MSKenv_t env = NULL;
MSKtask_t task = NULL;
MSKintt r = MSK_RES_OK;
/* Create mosek environment. */
r = MSK_makeenv(&env,NULL);
if ( r==MSK_RES_OK )
r = MSK_maketask(env,0,0,&task);
if ( r==MSK_RES_OK )
MSK_linkfunctotaskstream(task,MSK_STREAM_LOG,NULL,printstr);
if (r == MSK_RES_OK)
r = MSK_readdata(task,argv[1]);
MSK_putintparam(task,MSK_IPAR_OPTIMIZER,MSK_OPTIMIZER_CONCURRENT);
MSK_putintparam(task,MSK_IPAR_CONCURRENT_NUM_OPTIMIZERS,2);
if (r == MSK_RES_OK)
r = MSK_optimize(task);
MSK_solutionsummary(task,MSK_STREAM_LOG);
MSK_deletetask(&task);
MSK_deleteenv(&env);
printf("Return code: %d (0 means no error occured.)\n",r);
return ( r );
} /* main */
int mosekNNSolverWrapper(const Matrix &Q, const Matrix &Eq, const Matrix &b,
const Matrix &InEq, const Matrix &ib,
const Matrix &lowerBounds, const Matrix &upperBounds,
Matrix &sol, double *objVal, MosekObjectiveType objType)
{
DBGP("Mosek QP Wrapper started");
MSKrescodee r;
MSKtask_t task = NULL;
// Get the only instance of the mosek environment.
MSKenv_t env = getMosekEnv();
// Create the optimization task.
r = MSK_maketask(env, 0, 0, &task);
if (r != MSK_RES_OK) {
DBGA("Failed to create optimization task");
return -1;
}
MSK_linkfunctotaskstream(task, MSK_STREAM_LOG, NULL, printstr);
//---------------------------------------
//start inputing the problem
//prespecify number of variables to make inputting faster
r = MSK_putmaxnumvar(task, sol.rows());
//number of constraints (both equality and inequality)
if (r == MSK_RES_OK) {
r = MSK_putmaxnumcon(task, Eq.rows() + InEq.rows());
}
//make sure default value is 0 for sparse matrices
assert(Q.getDefault() == 0.0);
assert(Eq.getDefault() == 0.0);
assert(InEq.getDefault() == 0.0);
//number of non-zero entries in A
if (r == MSK_RES_OK) {
r = MSK_putmaxnumanz(task, Eq.numElements() + InEq.numElements());
}
if (r != MSK_RES_OK) {
DBGA("Failed to input variables");
MSK_deletetask(&task);
return -1;
}
//solver is sensitive to numerical problems. Scale the problem down
//we will use this value to scale down the right hand side of equality
//and inequality constraints and lower and upper bounds
//after solving, we must scale back up the solution and the value of the
//objective
double scale = b.absMax();
if (scale < 1.0e2) {
scale = 1.0;
} else {
DBGP("Mosek solver: scaling problem down by " << scale);
}
//---------------------------------------
//insert the actual variables and constraints
//append the variables
MSK_append(task, MSK_ACC_VAR, sol.rows());
//append the constraints.
MSK_append(task, MSK_ACC_CON, Eq.rows() + InEq.rows());
int i, j;
double value;
if (objType == MOSEK_OBJ_QP) {
//quadratic optimization objective
//the quadratic term
Q.sequentialReset();
while (Q.nextSequentialElement(i, j, value)) {
MSK_putqobjij(task, i, j, 2.0 * value);
}
} else if (objType == MOSEK_OBJ_LP) {
//linear objective
for (j = 0; j < Q.cols(); j++) {
if (fabs(Q.elem(0, j)) > 1.0e-5) {
MSK_putcj(task, j, Q.elem(0, j));
}
}
} else {
assert(0);
}
//variable bounds
assert(sol.rows() == lowerBounds.rows());
assert(sol.rows() == upperBounds.rows());
for (i = 0; i < sol.rows(); i++) {
if (lowerBounds.elem(i, 0) >= upperBounds.elem(i, 0)) {
if (lowerBounds.elem(i, 0) > upperBounds.elem(i, 0)) {
assert(0);
}
if (lowerBounds.elem(i, 0) == -std::numeric_limits<double>::max()) {
assert(0);
}
if (upperBounds.elem(i, 0) == std::numeric_limits<double>::max()) {
assert(0);
}
//fixed variable
DBGP(i << ": fixed " << lowerBounds.elem(i, 0) / scale);
MSK_putbound(task, MSK_ACC_VAR, i, MSK_BK_FX,
lowerBounds.elem(i, 0) / scale, upperBounds.elem(i, 0) / scale);
} else if (lowerBounds.elem(i, 0) != -std::numeric_limits<double>::max()) {
//finite lower bound
if (upperBounds.elem(i, 0) != std::numeric_limits<double>::max()) {
//two finite bounds
DBGP(i << ": finite bounds " << lowerBounds.elem(i, 0) / scale
<< " " << upperBounds.elem(i, 0) / scale);
MSK_putbound(task, MSK_ACC_VAR, i, MSK_BK_RA,
lowerBounds.elem(i, 0) / scale, upperBounds.elem(i, 0) / scale);
} else {
//lower bound
DBGP(i << ": lower bound " << lowerBounds.elem(i, 0) / scale);
MSK_putbound(task, MSK_ACC_VAR, i, MSK_BK_LO,
lowerBounds.elem(i, 0) / scale, +MSK_INFINITY);
}
} else {
//infinite lower bound
if (upperBounds.elem(i, 0) != std::numeric_limits<double>::max()) {
//upper bound
DBGP(i << ": upper bound " << upperBounds.elem(i, 0) / scale);
MSK_putbound(task, MSK_ACC_VAR, i, MSK_BK_UP,
-MSK_INFINITY, upperBounds.elem(i, 0) / scale);
} else {
//unbounded
DBGP(i << ": unbounded");
MSK_putbound(task, MSK_ACC_VAR, i, MSK_BK_FR,
-MSK_INFINITY, +MSK_INFINITY);
}
}
}
//constraints and constraint bounds
//equality constraints
Eq.sequentialReset();
while (Eq.nextSequentialElement(i, j, value)) {
MSK_putaij(task, i, j, value);
}
for (i = 0; i < Eq.rows(); i++) {
MSK_putbound(task, MSK_ACC_CON, i, MSK_BK_FX, b.elem(i, 0) / scale, b.elem(i, 0) / scale);
}
//inequality constraints, <=
InEq.sequentialReset();
while (InEq.nextSequentialElement(i, j, value)) {
int eqi = i + Eq.rows();
MSK_putaij(task, eqi, j, value);
}
for (i = 0; i < InEq.rows(); i++) {
int eqi = i + Eq.rows();
MSK_putbound(task, MSK_ACC_CON, eqi, MSK_BK_UP, -MSK_INFINITY, ib.elem(i, 0) / scale);
}
//specify objective: minimize
MSK_putobjsense(task, MSK_OBJECTIVE_SENSE_MINIMIZE);
//give it 800 iterations, twice the default.
MSK_putintparam(task, MSK_IPAR_INTPNT_MAX_ITERATIONS, 800);
//----------------------------------
//solve the thing
DBGP("Optimization started");
r = MSK_optimize(task);
DBGP("Optimization returns");
//write problem to file
/*
static int fileNum = 0;
if (r != MSK_RES_OK) {
char filename[50];
sprintf(filename,"mosek_error_%d_%d.opf",fileNum++, r);
MSK_writedata(task, filename);
FILE *fp = fopen(filename,"a");
fprintf(fp,"\n\nEquality matrix:\n");
Eq.print(fp);
fclose(fp);
}
*/
if (r != MSK_RES_OK) {
DBGA("Mosek optimization call failed, error code " << r);
MSK_deletetask(&task);
return -1;
}
DBGP("Optimization complete");
//debug code, find out number of iterations used
//int iter;
//MSK_getintinf(task, MSK_IINF_INTPNT_ITER, &iter);
//DBGA("Iterations used: " << iter);
//find out what kind of solution we have
MSKprostae pst;
MSKsolstae sst;
MSK_getsolutionstatus(task, MSK_SOL_ITR, &pst, &sst);
int result;
if (sst == MSK_SOL_STA_OPTIMAL || sst == MSK_SOL_STA_NEAR_OPTIMAL) {
//success, we have an optimal problem
if (sst == MSK_SOL_STA_OPTIMAL) {DBGP("QP solution is optimal");}
else {DBGA("QP solution is *nearly* optimal");}
result = 0;
} else if (sst == MSK_SOL_STA_PRIM_INFEAS_CER) {
//unfeasible problem
DBGP("Mosek optimization: primal infeasible");
result = 1;
} else if (sst == MSK_SOL_STA_DUAL_INFEAS_CER) {
//unfeasible problem
DBGA("Mosek optimization: dual infeasible (primal unbounded?)");
result = 1;
} else if (sst == MSK_SOL_STA_PRIM_AND_DUAL_FEAS) {
//i think this means feasible problem, but unbounded solution
//this shouldn't happen as our Q is positive semidefinite
DBGA("QP solution is prim and dual feasible, but not optimal");
DBGA("Is Q positive semidefinite?");
result = -1;
} else {
//unknown return status
DBGA("QP fails with solution status " << sst << " and problem status " << pst);
result = -1;
}
//MSK_SOL_STA_DUAL_FEAS;
//retrieve the solutions
if (!result) {
//get the value of the objective function
MSKrealt obj, foo;
MSK_getsolutioninf(task, MSK_SOL_ITR, &pst, &sst, &obj,
&foo, &foo, &foo, &foo, &foo, &foo, &foo, &foo);
if (objType == MOSEK_OBJ_QP) {
*objVal = obj * scale * scale;
} else if (objType == MOSEK_OBJ_LP) {
*objVal = obj * scale;
} else {
assert(0);
}
double *xx = new double[sol.rows()];
MSK_getsolutionslice(task, MSK_SOL_ITR, MSK_SOL_ITEM_XX,
0, sol.rows(), xx);
for (i = 0; i < sol.rows(); i++) {
sol.elem(i, 0) = scale * xx[i];
DBGP("x" << i << ": " << xx[i]);
}
delete [] xx;
}
MSK_deletetask(&task);
return result;
}
int main(int argc,char *argv[])
{
const MSKint32t numvar = 3,
numcon = 3;
MSKint32t i,j;
double c[] = {1.5, 2.5, 3.0};
MSKint32t ptrb[] = {0, 3, 6},
ptre[] = {3, 6, 9},
asub[] = { 0, 1, 2,
0, 1, 2,
0, 1, 2};
double aval[] = { 2.0, 3.0, 2.0,
4.0, 2.0, 3.0,
3.0, 3.0, 2.0};
MSKboundkeye bkc[] = {MSK_BK_UP, MSK_BK_UP, MSK_BK_UP };
double blc[] = {-MSK_INFINITY, -MSK_INFINITY, -MSK_INFINITY};
double buc[] = {100000, 50000, 60000};
MSKboundkeye bkx[] = {MSK_BK_LO, MSK_BK_LO, MSK_BK_LO};
double blx[] = {0.0, 0.0, 0.0,};
double bux[] = {+MSK_INFINITY, +MSK_INFINITY,+MSK_INFINITY};
double *xx=NULL;
MSKenv_t env;
MSKtask_t task;
MSKint32t varidx,conidx;
MSKrescodee r;
/* Create the mosek environment. */
r = MSK_makeenv(&env,NULL);
if ( r==MSK_RES_OK )
{
/* Create the optimization task. */
r = MSK_maketask(env,numcon,numvar,&task);
/* Directs the log task stream to the
'printstr' function. */
MSK_linkfunctotaskstream(task,MSK_STREAM_LOG,NULL,printstr);
/* Append the constraints. */
if (r == MSK_RES_OK)
r = MSK_appendcons(task,numcon);
/* Append the variables. */
if (r == MSK_RES_OK)
r = MSK_appendvars(task,numvar);
/* Put C. */
if (r == MSK_RES_OK)
r = MSK_putcfix(task, 0.0);
if (r == MSK_RES_OK)
for(j=0; j<numvar; ++j)
r = MSK_putcj(task,j,c[j]);
/* Put constraint bounds. */
if (r == MSK_RES_OK)
for(i=0; i<numcon; ++i)
r = MSK_putconbound(task,i,bkc[i],blc[i],buc[i]);
/* Put variable bounds. */
if (r == MSK_RES_OK)
for(j=0; j<numvar; ++j)
r = MSK_putvarbound(task,j,bkx[j],blx[j],bux[j]);
/* Put A. */
if (r == MSK_RES_OK)
if ( numcon>0 )
for(j=0; j<numvar; ++j)
r = MSK_putacol(task,
j,
ptre[j]-ptrb[j],
asub+ptrb[j],
aval+ptrb[j]);
if (r == MSK_RES_OK)
r = MSK_putobjsense(task,
MSK_OBJECTIVE_SENSE_MAXIMIZE);
if (r == MSK_RES_OK)
r = MSK_optimizetrm(task,NULL);
if (r == MSK_RES_OK)
{
xx = calloc(numvar,sizeof(double));
if ( !xx )
r = MSK_RES_ERR_SPACE;
}
if (r == MSK_RES_OK)
r = MSK_getxx(task,
MSK_SOL_BAS, /* Basic solution. */
xx);
/* Make a change to the A matrix */
if (r == MSK_RES_OK)
r = MSK_putaij(task, 0, 0, 3.0);
if (r == MSK_RES_OK)
r = MSK_optimizetrm(task,NULL);
/* Get index of new variable, this should be 3 */
if (r == MSK_RES_OK)
r = MSK_getnumvar(task,&varidx);
/* Append a new variable x_3 to the problem */
if (r == MSK_RES_OK)
r = MSK_appendvars(task,1);
/* Set bounds on new variable */
if (r == MSK_RES_OK)
r = MSK_putvarbound(task,
varidx,
MSK_BK_LO,
0,
+MSK_INFINITY);
/* Change objective */
if (r == MSK_RES_OK)
r = MSK_putcj(task,varidx,1.0);
/* Put new values in the A matrix */
if (r == MSK_RES_OK)
{
MSKint32t acolsub[] = {0, 2};
double acolval[] = {4.0, 1.0};
r = MSK_putacol(task,
varidx, /* column index */
2, /* num nz in column*/
acolsub,
acolval);
}
/* Change optimizer to free simplex and reoptimize */
if (r == MSK_RES_OK)
r = MSK_putintparam(task,MSK_IPAR_OPTIMIZER,MSK_OPTIMIZER_FREE_SIMPLEX);
if (r == MSK_RES_OK)
r = MSK_optimizetrm(task,NULL);
/* Get index of new constraint*/
if (r == MSK_RES_OK)
r = MSK_getnumcon(task,&conidx);
/* Append a new constraint */
if (r == MSK_RES_OK)
r = MSK_appendcons(task,1);
/* Set bounds on new constraint */
if (r == MSK_RES_OK)
r = MSK_putconbound(task,
conidx,
MSK_BK_UP,
-MSK_INFINITY,
30000);
/* Put new values in the A matrix */
if (r == MSK_RES_OK)
{
MSKidxt arowsub[] = {0, 1, 2, 3 };
double arowval[] = {1.0, 2.0, 1.0, 1.0};
r = MSK_putarow(task,
conidx, /* row index */
4, /* num nz in row*/
arowsub,
arowval);
}
if (r == MSK_RES_OK)
r = MSK_optimizetrm(task,NULL);
if ( xx )
free(xx);
MSK_deletetask(&task);
}
MSK_deleteenv(&env);
printf("Return code: %d (0 means no error occured.)\n",r);
return ( r );
} /* main */
int main(int argc,char **argv)
{
MSKintt r=MSK_RES_OK,i;
MSKenv_t env = NULL;
MSKtask_t task = NULL;
MSKtask_t task_list[NUMTASKS];
/* Ensure that we can delete tasks even if they are not allocated */
task_list[0] = NULL;
/* Create mosek environment. */
r = MSK_makeenv(&env,NULL);
/* Create a task for each concurrent optimization.
The 'task' is the master task that will hold the problem data.
*/
if ( r==MSK_RES_OK )
r = MSK_maketask(env,0,0,&task);
if (r == MSK_RES_OK)
r = MSK_maketask(env,0,0,&task_list[0]);
/* Assign call-back functions to each task */
if (r == MSK_RES_OK)
MSK_linkfunctotaskstream(task,
MSK_STREAM_LOG,
NULL,
printstr1);
if (r == MSK_RES_OK)
MSK_linkfunctotaskstream(task_list[0],
MSK_STREAM_LOG,
NULL,
printstr2);
if (r == MSK_RES_OK)
r = MSK_linkfiletotaskstream(task,
MSK_STREAM_LOG,
"simplex.log",
0);
if (r == MSK_RES_OK)
r = MSK_linkfiletotaskstream(task_list[0],
MSK_STREAM_LOG,
"intpnt.log",
0);
if (r == MSK_RES_OK)
r = MSK_readdata(task,argv[1]);
/* Assign different parameter values to each task.
In this case different optimizers. */
if (r == MSK_RES_OK)
r = MSK_putintparam(task,
MSK_IPAR_OPTIMIZER,
MSK_OPTIMIZER_PRIMAL_SIMPLEX);
if (r == MSK_RES_OK)
r = MSK_putintparam(task_list[0],
MSK_IPAR_OPTIMIZER,
MSK_OPTIMIZER_INTPNT);
/* Optimize task and task_list[0] in parallel.
The problem data i.e. C, A, etc.
is copied from task to task_list[0].
*/
if (r == MSK_RES_OK)
r = MSK_optimizeconcurrent (task,
task_list,
NUMTASKS);
printf ("Return Code = %d\n",r);
MSK_solutionsummary(task,
MSK_STREAM_LOG);
MSK_deletetask(&task);
MSK_deletetask(&task_list[0]);
MSK_deleteenv(&env);
return r;
}
template <typename _Scalar> typename MosekOpt<_Scalar>::ReturnType
MosekOpt<_Scalar>::
update( bool verbose )
{
if ( _task != NULL )
{
std::cerr << "[" << __func__ << "]: " << "update can only be called once! returning." << std::endl;
return MSK_RES_ERR_UNKNOWN;
}
/* Create the optimization task. */
if ( MSK_RES_OK == _r )
{
_r = MSK_maketask( _env, this->getConstraintCount(), this->getVarCount(), &_task );
if ( MSK_RES_OK != _r )
std::cerr << "[" << __func__ << "]: " << "could not create task with " << this->getVarCount() << " vars, and " << this->getConstraintCount() << " constraints" << std::endl;
}
// redirect output
if ( MSK_RES_OK == _r )
{
_r = MSK_linkfunctotaskstream( _task, MSK_STREAM_LOG, NULL, mosekPrintStr );
if ( MSK_RES_OK != _r )
std::cerr << "[" << __func__ << "]: " << "could not create rewire output to mosekPrintStr(), continuing though..." << std::endl;
}
// Append _numCon empty constraints. The constraints will initially have no bounds.
if ( MSK_RES_OK == _r )
{
if ( verbose ) std::cout << "my: MSK_appendcons(_task,"<< this->getConstraintCount() <<");" << std::endl;
_r = MSK_appendcons( _task, this->getConstraintCount() );
if ( MSK_RES_OK != _r )
std::cerr << "[" << __func__ << "]: " << "could not append " << this->getConstraintCount() << " constraints" << std::endl;
}
// Append _numVar variables. The variables will initially be fixed at zero (x=0).
if ( MSK_RES_OK == _r )
{
if ( verbose ) std::cout << "my: MSK_appendvars(_task," << this->getVarCount() <<");" << std::endl;
_r = MSK_appendvars( _task, this->getVarCount() );
if ( MSK_RES_OK != _r )
std::cerr << "[" << __func__ << "]: " << "could not append " << this->getVarCount() << " variables" << std::endl;
}
// Optionally add a constant term to the objective.
if ( MSK_RES_OK == _r )
{
if ( verbose ) std::cout << "my: MSK_putcfix(_task," << this->getObjectiveBias() << ");" << std::endl;
_r = MSK_putcfix( _task, this->getObjectiveBias() );
if ( MSK_RES_OK != _r )
std::cerr << "[" << __func__ << "]: " << "could not add constant " << this->getObjectiveBias() << " to objective function" << std::endl;
}
// set Variables
for ( size_t j = 0; (j < this->getVarCount()) && (MSK_RES_OK == _r); ++j )
{
// set Variable j's Bounds // blx[j] <= x_j <= bux[j]
if ( MSK_RES_OK == _r )
{
_r = MSK_putvarbound( _task,
j, /* Index of variable.*/
MosekOpt<Scalar>::getBoundTypeCustom( this->getVarBoundType(j) ), /* Bound key.*/
this->getVarLowerBound(j), /* Numerical value of lower bound.*/
this->getVarUpperBound(j) ); /* Numerical value of upper bound.*/
if ( verbose ) std::cout << "my: MSK_putvarbound(_task," << j << "," << this->getVarBoundType(j) << "," << this->getVarLowerBound(j) << "," << this->getVarUpperBound(j) << ");" << std::endl;
}
// set Variable j's Type
if ( MSK_RES_OK == _r )
{
_r = MSK_putvartype( _task, j, MosekOpt<Scalar>::getVarTypeCustom(this->getVarType(j)) );
}
// set Variable j's linear coefficient in the objective function
if ( MSK_RES_OK == _r )
{
if ( verbose ) std::cout << "my: putcj(_task," << j << "," << this->getLinObjectives()[j] << ")" << std::endl;
_r = MSK_putcj( _task, j, this->getLinObjectives()[j] );
}
}
// set Quadratic Objectives
if ( MSK_RES_OK == _r )
{
const int numNonZeros = this->getQuadraticObjectives().size();
MSKint32t *qsubi = new MSKint32t[numNonZeros],
*qsubj = new MSKint32t[numNonZeros];
double *qval = new double[numNonZeros];
for ( size_t qi = 0; qi != this->getQuadraticObjectives().size(); ++qi )
{
qsubi[qi] = this->getQuadraticObjectives()[qi].row();
qsubj[qi] = this->getQuadraticObjectives()[qi].col();
qval [qi] = this->getQuadraticObjectives()[qi].value();
}
if ( verbose ) std::cout<<"my: putqobj( _task, " << numNonZeros << ",\n";
for ( size_t vi = 0; vi != numNonZeros; ++vi )
{
if ( verbose ) std::cout << qsubi[vi] << "," << qsubj[vi] << ", " << qval[vi] << std::endl;
}
if ( verbose ) std::cout << ");" << std::endl;
_r = MSK_putqobj( _task, numNonZeros, qsubi, qsubj, qval );
if ( qsubi ) { delete[] qsubi; qsubi = NULL; }
if ( qsubj ) { delete[] qsubj; qsubj = NULL; }
if ( qval ) { delete[] qval ; qval = NULL; }
if ( MSK_RES_OK != _r )
std::cerr << "[" << __func__ << "]: " << "Setting Quadratic Objectives caused error code " << (int)_r << std::endl;
} // ...Quadratic objective
// set Linear Constraints
{
typename ParentType::SparseMatrix A( this->getLinConstraintsMatrix() );
// ( this->getConstraintCount(), this->getVarCount() );
// A.setFromTriplets( this->getLinConstraints().begin(), this->getLinConstraints().end() );
std::vector<double> aval; // Linear constraints coeff matrix (sparse)
std::vector<int> asub; // Linear constraints coeff matrix indices
std::vector<int> aptrb, aptre;
for ( int row = 0; (row < A.outerSize()) && (MSK_RES_OK == _r); ++row )
{
// set Constraint Bounds for row
if ( MSK_RES_OK == _r )
{
if ( verbose ) std::cout << "my: MSK_putconbound( _task, " << row << ", "
<< MosekOpt<Scalar>::getBoundTypeCustom( this->getConstraintBoundType(row) ) << ", "
<< this->getConstraintLowerBound( row ) << ", "
<< this->getConstraintUpperBound( row ) << ")"
<< std::endl; fflush( stdout );
_r = MSK_putconbound( _task,
row, /* Index of constraint.*/
MosekOpt<Scalar>::getBoundTypeCustom(this->getConstraintBoundType(row)), /* Bound key.*/
this->getConstraintLowerBound(row), /* Numerical value of lower bound.*/
this->getConstraintUpperBound(row) ); /* Numerical value of upper bound.*/
}
// set Linear Constraint row
if ( MSK_RES_OK == _r )
{
// new line starts at index == current size
aptrb.push_back( aval.size() );
// add coeffs from new line
for ( typename ParentType::SparseMatrix::InnerIterator it(A,row); it; ++it )
{
if ( row != it.row() ) std::cerr << "[" << __func__ << "]: " << "this shouldn't happen" << std::endl;
// coeff value
aval.push_back( it.value() ); // TODO: A should be a matrix, not a vector...
// coeff subscript
asub.push_back( it.col() );
}
// new line ends at index == new size
aptre.push_back( aval.size() );
if ( verbose ) {
std::cout << "my: MSK_putarow( _task, "
<< row << ", "
<< aptre[row] - aptrb[row] << ", "
<< *(asub.data() + aptrb[row]) << ", "
<< *(aval.data() + aptrb[row]) << ");"
<< std::endl; fflush( stdout );
}
_r = MSK_putarow( _task,
row, /* Row index.*/
aptre[row] - aptrb[row], /* Number of non-zeros in row i.*/
asub.data() + aptrb[row], /* Pointer to column indexes of row i.*/
aval.data() + aptrb[row]); /* Pointer to values of row i.*/
}
} // ... for A.rows
// report error
if ( MSK_RES_OK != _r )
std::cerr << "[" << __func__ << "]: " << "Setting Lin constraints caused error code " << (int)_r << std::endl;
} // ...set Linear Constraints
// set Quadratic constraints
if ( verbose ) std::cout << "[" << __func__ << "]: " << "adding q constraints" << std::endl;
for ( size_t constr_id = 0; (constr_id != this->getQuadraticConstraints().size()) && (MSK_RES_OK == _r); ++constr_id )
{
const int numNonZeros = this->getQuadraticConstraints(constr_id).size();
MSKint32t *qsubi = new MSKint32t[numNonZeros],
*qsubj = new MSKint32t[numNonZeros];
double *qval = new double[numNonZeros];
for ( size_t qi = 0; qi != this->getQuadraticConstraints(constr_id).size(); ++qi )
{
qsubi[qi] = this->getQuadraticConstraints(constr_id)[qi].row();
qsubj[qi] = this->getQuadraticConstraints(constr_id)[qi].col();
qval [qi] = this->getQuadraticConstraints(constr_id)[qi].value();
}
if ( verbose ) std::cout<<"my: MSK_putqonk( _task, " << constr_id << ", " << numNonZeros << ",\n";
for(size_t vi=0;vi!=numNonZeros;++vi)
{
if ( verbose ) std::cout << qsubi[vi] << "," << qsubj[vi] << ", " << qval[vi] << std::endl;
}
if ( verbose ) std::cout << "); " << std::endl;
_r = MSK_putqconk(_task,
constr_id,
numNonZeros,
qsubi,
qsubj,
qval);
if ( qsubi ) { delete[] qsubi; qsubi = NULL; }
if ( qsubj ) { delete[] qsubj; qsubj = NULL; }
if ( qval ) { delete[] qval ; qval = NULL; }
if ( MSK_RES_OK != _r )
std::cerr << "[" << __func__ << "]: " << "Setting Quad constraints caused error code " << (int)_r << std::endl;
} // ...set Quadratic Constraints
// save to file
{
if ( _r == MSK_RES_OK )
{
_r = MSK_putintparam( _task, MSK_IPAR_WRITE_DATA_FORMAT, MSK_DATA_FORMAT_LP );
if ( _r == MSK_RES_OK )
{
_r = MSK_writedata( _task, "mosek.lp" );
if ( _r != MSK_RES_OK )
{
std::cerr << "[" << __func__ << "]: " << "Writedata did not work" << (int)_r << std::endl;
}
}
}
}
if ( _r == MSK_RES_OK )
{
this->_x.setZero();
this->_updated = true;
}
// return error code
return _r;
} // ...MosekOpt::update()
template <typename _Scalar> typename MosekOpt<_Scalar>::ReturnType
MosekOpt<_Scalar>::optimize( std::vector<_Scalar> *x_out, OBJ_SENSE objective_sense )
{
if ( !this->_updated )
{
std::cerr << "[" << __func__ << "]: " << "Please call update() first!" << std::endl;
return MSK_RES_ERR_UNKNOWN;
}
// cache problem size
const int numvar = this->getVarCount();
// determine problem type
MSKobjsense_enum objsense = (objective_sense == OBJ_SENSE::MINIMIZE) ? MSK_OBJECTIVE_SENSE_MINIMIZE
: MSK_OBJECTIVE_SENSE_MAXIMIZE;
if ( MSK_RES_OK == _r )
_r = MSK_putobjsense( _task, objsense );
if ( MSK_RES_OK == _r )
{
// set termination sensitivity
MSKrescodee trmcode;
if ( (_r == MSK_RES_OK) && (this->getTolRelGap() > Scalar(0)) )
{
_r = MSK_putdouparam( _task, MSK_DPAR_MIO_TOL_REL_GAP, this->getTolRelGap() /*1e-10f*/ );
if ( _r != MSK_RES_OK )
{
std::cerr << "[" << __func__ << "]: " << "setting MSK_DPAR_MIO_DISABLE_TERM_TIME to " << this->getTimeLimit() << " did NOT work!" << std::endl;
}
}
if ( (_r == MSK_RES_OK) && (this->getTimeLimit() > Scalar(0)) )
{
_r = MSK_putdouparam(_task, MSK_DPAR_MIO_DISABLE_TERM_TIME, this->getTimeLimit() );
if ( _r != MSK_RES_OK )
{
std::cerr << "[" << __func__ << "]: " << "setting MSK_DPAR_MIO_DISABLE_TERM_TIME to " << this->getTimeLimit() << " did NOT work!" << std::endl;
}
_r = MSK_putdouparam(_task, MSK_DPAR_MIO_MAX_TIME, this->getTimeLimit()+Scalar(5) );
if ( _r != MSK_RES_OK )
{
std::cerr << "[" << __func__ << "]: " << "setting MSK_DPAR_MIO_MAX_TIME to " << this->getTimeLimit()+Scalar(5) << " did NOT work!" << std::endl;
}
}
if (_r == MSK_RES_OK)
{
//_r = MSK_putintparam(_task, MSK_IPAR_OPTIMIZER, MSK_OPTIMIZER_MIXED_INT_CONIC );
if ( _r != MSK_RES_OK )
{
std::cerr << "[" << __func__ << "]: " << "setting MSK_OPTIMIZER_MIXED_INT_CONIC did not work!" << std::endl;
}
}
if ( _r == MSK_RES_OK )
{
_r = MSK_putintparam( _task, MSK_IPAR_MIO_PRESOLVE_USE, MSK_ON );
if ( _r != MSK_RES_OK )
{
std::cerr << "[" << __func__ << "]: " << "setting MSK_IPAR_MIO_PRESOLVE_USE did not work!" << std::endl;
}
}
if ( _r == MSK_RES_OK )
{
_r = MSK_putintparam( _task, MSK_IPAR_MIO_HEURISTIC_LEVEL, 5 );
if ( _r != MSK_RES_OK )
{
std::cerr << "[" << __func__ << "]: " << "setting MSK_IPAR_MIO_HEURISTIC_LEVEL did not work!" << std::endl;
}
}
// Run optimizer
_r = MSK_optimizetrm( _task, &trmcode );
// Print a summary containing information about the solution for debugging purposes.
MSK_solutionsummary( _task, MSK_STREAM_LOG );
// save solution
double *xx = (double*) calloc(numvar,sizeof(double));
if ( _r == MSK_RES_OK )
{
MSKsolstae solsta;
if ( _r == MSK_RES_OK )
{
_r = MSK_getsolsta( _task, MSK_SOL_ITR, &solsta );
if ( _r != MSK_RES_OK )
{
_r = MSK_getsolsta( _task, MSK_SOL_ITG, &solsta );
}
if ( _r != MSK_RES_OK )
{
std::cerr << "[" << __func__ << "]: " << "neithter MSK_SOL_ITR, nor MSK_SOL_ITR worked" << std::endl;
}
}
switch ( solsta )
{
case MSK_SOL_STA_OPTIMAL:
case MSK_SOL_STA_NEAR_OPTIMAL:
{
if ( xx )
{
MSK_getxx(_task,
MSK_SOL_ITR, /* Request the basic solution. */
xx);
_storeSolution( xx, numvar );
printf("Optimal primal solution\n");
}
else
{
_r = MSK_RES_ERR_SPACE;
}
break;
}
case MSK_SOL_STA_DUAL_INFEAS_CER:
case MSK_SOL_STA_PRIM_INFEAS_CER:
case MSK_SOL_STA_NEAR_DUAL_INFEAS_CER:
case MSK_SOL_STA_NEAR_PRIM_INFEAS_CER:
printf("Primal or dual infeasibility certificate found.\n");
break;
case MSK_SOL_STA_UNKNOWN:
{
MSKprostae prosta;
MSK_getprosta(_task,MSK_SOL_ITG,&prosta);
switch (prosta)
{
case MSK_PRO_STA_PRIM_INFEAS_OR_UNBOUNDED:
printf("Problem status Infeasible or unbounded\n");
break;
case MSK_PRO_STA_PRIM_INFEAS:
printf("Problem status Infeasible.\n");
break;
case MSK_PRO_STA_UNKNOWN:
printf("Problem status unknown.\n");
break;
default:
printf("Other problem status.");
break;
}
char symname[MSK_MAX_STR_LEN];
char desc[MSK_MAX_STR_LEN];
/* If the solutions status is unknown, print the termination code
indicating why the optimizer terminated prematurely. */
MSK_getcodedesc(trmcode,
symname,
desc);
printf("The solutuion status is unknown.\n");
printf("The optimizer terminitated with code: %s\n",symname);
break;
}
// ITG
//asdf todo: consolidate this last part:
case MSK_SOL_STA_INTEGER_OPTIMAL:
case MSK_SOL_STA_NEAR_INTEGER_OPTIMAL :
MSK_getxx(_task,
MSK_SOL_ITG, /* Request the integer solution. */
xx);
_storeSolution( xx, numvar );
printf("Optimal integer solution.\n");
break;
case MSK_SOL_STA_PRIM_FEAS:
/* A feasible but not necessarily optimal solution was located. */
MSK_getxx(_task,MSK_SOL_ITG,xx);
_storeSolution( xx, numvar );
printf("Feasible solution.\n");
break;
default:
std::cerr << "[" << __func__ << "]: " << "unknown code " << (int)solsta << std::endl;
break;
}
if ( xx ) { free(xx); xx = NULL; }
}
}
if ( MSK_RES_OK != _r )
{
/* In case of an error print error code and description. */
char symname[MSK_MAX_STR_LEN];
char desc[MSK_MAX_STR_LEN];
printf("An error occurred while optimizing.\n");
MSK_getcodedesc( _r,
symname,
desc);
printf("Error %s - '%s'\n",symname,desc);
}
else
{
// output
if ( x_out )
{
x_out->clear();
x_out->reserve( this->_x.size() );
for ( int j=0; j < this->_x.size(); ++j )
{
x_out->push_back( this->_x[j] );
}
}
}
return _r;
} // ...MosekOpt::optimize()
int main(int argc,char *argv[])
{
MSKrescodee
r;
MSKboundkeye
bkc[NUMCON],bkx[NUMVAR];
int
j,i,
ptrb[NUMVAR],ptre[NUMVAR],sub[NUMANZ];
double
blc[NUMCON],buc[NUMCON],
c[NUMVAR],blx[NUMVAR],bux[NUMVAR],val[NUMANZ],
xx[NUMVAR];
MSKenv_t env;
MSKtask_t task;
/* Make mosek environment. */
r = MSK_makeenv(&env,NULL,NULL,NULL,NULL);
/* Check is return code is ok. */
if ( r==MSK_RES_OK )
{
/* Directs the env log stream to the user
specified procedure 'printstr'. */
MSK_linkfunctoenvstream(env,MSK_STREAM_LOG,NULL,printstr);
}
/* Initialize the environment. */
r = MSK_initenv(env);
if ( r==MSK_RES_OK )
{
/* Send a message to the MOSEK Message stream. */
MSK_echoenv(env,
MSK_STREAM_MSG,
"\nMaking the MOSEK optimization task\n");
/* Make the optimization task. */
r = MSK_maketask(env,NUMCON,NUMVAR,&task);
if ( r==MSK_RES_OK )
{
/* Directs the log task stream to the user
specified procedure 'printstr'. */
MSK_linkfunctotaskstream(task,MSK_STREAM_LOG,NULL,printstr);
MSK_echotask(task,
MSK_STREAM_MSG,
"\nDefining the problem data.\n");
/* Define bounds for the constraints. */
/* Constraint: 0 */
bkc[0] = MSK_BK_FX; /* Type of bound. */
blc[0] = 30.0; /* Lower bound on the
constraint. */
buc[0] = 30.0; /* Upper bound on the
constraint. */
/* Constraint: 1 */
bkc[1] = MSK_BK_LO;
blc[1] = 15.0;
buc[1] = MSK_INFINITY;
/* Constraint: 2 */
bkc[2] = MSK_BK_UP;
blc[2] = -MSK_INFINITY;
buc[2] = 25.0;
/* Define information for the variables. */
/* Variable: x0 */
c[0] = 3.0; /* The objective function. */
ptrb[0] = 0; ptre[0] = 2; /* First column in
the constraint matrix. */
sub[0] = 0; val[0] = 3.0;
sub[1] = 1; val[1] = 2.0;
bkx[0] = MSK_BK_LO; /* Type of bound. */
blx[0] = 0.0; /* Lower bound on the
variables. */
bux[0] = MSK_INFINITY; /* Upper bound on the
variables. */
/* Variable: x1 */
c[1] = 1.0;
ptrb[1] = 2; ptre[1] = 5;
sub[2] = 0; val[2] = 1.0;
sub[3] = 1; val[3] = 1.0;
sub[4] = 2; val[4] = 2.0;
bkx[1] = MSK_BK_RA;
blx[1] = 0.0;
bux[1] = 10;
/* Variable: x2 */
c[2] = 5.0;
ptrb[2] = 5; ptre[2] = 7;
sub[5] = 0; val[5] = 2.0;
sub[6] = 1; val[6] = 3.0;
bkx[2] = MSK_BK_LO;
blx[2] = 0.0;
bux[2] = MSK_INFINITY;
/* Variable: x3 */
c[3] = 1.0;
ptrb[3] = 7; ptre[3] = 9;
sub[7] = 1; val[7] = 1.0;
sub[8] = 2; val[8] = 3.0;
bkx[3] = MSK_BK_LO;
blx[3] = 0.0;
bux[3] = MSK_INFINITY;
MSK_putobjsense(task,
MSK_OBJECTIVE_SENSE_MAXIMIZE);
/* Use the primal simplex optimizer. */
MSK_putintparam(task,
MSK_IPAR_OPTIMIZER,
MSK_OPTIMIZER_PRIMAL_SIMPLEX);
MSK_echotask(task,
MSK_STREAM_MSG,
"\nAdding constraints\n");
r = MSK_append(task,
MSK_ACC_CON,
NUMCON);
/* Adding bounds on empty constraints */
for(i=0; r==MSK_RES_OK && i<NUMCON; ++i)
{
r = MSK_putbound(task,
MSK_ACC_CON,
i,
bkc[i],
blc[i],
buc[i]);
}
/* Dynamically adding columns */
for(j= 0; r==MSK_RES_OK && j<NUMVAR; ++j)
{
MSK_echotask(task,
MSK_STREAM_MSG,
"\nAdding a new variable.\n");
r = MSK_append(task,MSK_ACC_VAR,1);
if ( r==MSK_RES_OK )
r = MSK_putcj(task,j,c[j]);
if ( r==MSK_RES_OK )
r = MSK_putavec(task,
MSK_ACC_VAR,
j,
ptre[j]-ptrb[j],
sub+ptrb[j],
val+ptrb[j]);
if ( r==MSK_RES_OK )
r = MSK_putbound(task,
MSK_ACC_VAR,
j,
bkx[j],
blx[j],
bux[j]);
if( r == MSK_RES_OK )
{
MSK_echotask(task,
MSK_STREAM_MSG,
"\nOptimizing\n");
r = MSK_optimize(task);
MSK_solutionsummary(task,MSK_STREAM_MSG);
}
}
MSK_deletetask(&task);
}
}
MSK_deleteenv(&env);
printf("Return code: %d (0 means no error occured.)\n",r);
return ( r );
} /* main */