/*
n: size of b and coords, may be smaller than mskEnv->num_variables if we
have dummy vars
b: coefficients of linear part of optimisation function
coords: optimal y* vector, coord[i] is coordinate of node[i]
*/
void mosek_quad_solve_sep(MosekEnv * mskEnv, int n, float *b,
float *coords)
{
int i, j;
assert(n <= mskEnv->num_variables + 1);
for (i = 0; i < n - 1 && mskEnv->r == MSK_RES_OK; i++) {
mskEnv->r = MSK_putcj(mskEnv->task, i, -2 * b[i + 1]);
}
if (mskEnv->r == MSK_RES_OK)
mskEnv->r = MSK_optimize(mskEnv->task);
if (mskEnv->r == MSK_RES_OK) {
MSK_getsolutionslice(mskEnv->task,
MSK_SOL_ITR,
MSK_SOL_ITEM_XX,
0, mskEnv->num_variables, mskEnv->xx);
#ifdef DUMP_CONSTRAINTS
fprintf(logfile, "Primal solution\n");
#endif
coords[0] = 0;
for (j = 1; j <= n; j++) {
#ifdef DUMP_CONSTRAINTS
fprintf(logfile, "x[%d]: %.2f\n", j, mskEnv->xx[j - 1]);
#endif
coords[j] = -mskEnv->xx[j - 1];
}
}
fprintf(logfile, "Return code: %d\n", mskEnv->r);
}
/*
b: coefficients of linear part of optimisation function
n: number of nodes
coords: optimal y* vector, coord[i] is coordinate of node[i]
hierarchy_boundaries: y coord of boundaries between levels
(ie, solution values for the dummy variables used in constraints)
*/
void mosek_quad_solve_hier(MosekEnv * mskEnv, float *b, int n,
float *coords, float *hierarchy_boundaries)
{
int i, j;
for (i = 1; i < n && mskEnv->r == MSK_RES_OK; i++) {
mskEnv->r = MSK_putcj(mskEnv->task, i - 1, -2 * b[i]);
}
#ifdef DUMP_CONSTRAINTS
fprintf(logfile, "x0=[");
for (j = 0; j < mskEnv->num_variables; j++) {
fprintf(logfile, "%f ", j < n ? b[j] : 0);
}
fprintf(logfile, "]\n");
fprintf(logfile, "f=[");
double *c = N_GNEW(mskEnv->num_variables, double);
MSK_getc(mskEnv->task, c);
for (j = 0; j < mskEnv->num_variables; j++) {
fprintf(logfile, "%f ", c[j]);
}
free(c);
fprintf(logfile, "]\n");
#endif
if (mskEnv->r == MSK_RES_OK)
mskEnv->r = MSK_optimize(mskEnv->task);
if (mskEnv->r == MSK_RES_OK) {
MSK_getsolutionslice(mskEnv->task,
MSK_SOL_ITR,
MSK_SOL_ITEM_XX,
0, mskEnv->num_variables, mskEnv->xx);
#ifdef DUMP_CONSTRAINTS
fprintf(logfile, "Primal solution\n");
#endif
coords[0] = 0;
for (j = 0; j < mskEnv->num_variables; ++j) {
#ifdef DUMP_CONSTRAINTS
fprintf(logfile, "x[%d]: %.2f\n", j, mskEnv->xx[j]);
#endif
if (j < n - 1) {
coords[j + 1] = -mskEnv->xx[j];
} else if (j >= n && j < mskEnv->num_variables - 1) {
hierarchy_boundaries[j - n] = -mskEnv->xx[j];
}
}
}
fprintf(logfile, "Return code: %d\n", mskEnv->r);
}
bool ConicSolver::Solve(VectorXd& sol)
{
bool ret = false;
#ifdef _WIN32
VectorXd solution;
convertMatrixVectorFormat();
MSKenv_t env;
MSKtask_t task;
MSKrescodee r;
r = MSK_makeenv(&env, NULL, NULL, NULL, NULL);
if (r == MSK_RES_OK)
{
r = MSK_linkfunctoenvstream(env, MSK_STREAM_LOG, NULL, printstr);
}
r = MSK_initenv(env);
if (r == MSK_RES_OK)
{
r = MSK_maketask(env, mNumCon, mNumVar, &task);
if (r == MSK_RES_OK)
{
r = MSK_linkfunctotaskstream(task, MSK_STREAM_LOG, NULL, printstr);
}
if (r == MSK_RES_OK)
r = MSK_putmaxnumvar(task, mNumVar);
if (r == MSK_RES_OK)
r = MSK_putmaxnumcon(task, mNumCon);
/* Append ¡¯NUMCON ¡¯ empty constraints .
The constraints will initially have no bounds . */
if (r == MSK_RES_OK)
r = MSK_append(task, MSK_ACC_CON, mNumCon);
/* Append ¡¯NUMVAR ¡¯ variables .
The variables will initially be fixed at zero (x =0). */
if (r == MSK_RES_OK)
r = MSK_append(task, MSK_ACC_VAR, mNumVar);
/* Optionally add a constant term to the objective . */
if (r == MSK_RES_OK)
r = MSK_putcfix(task, mConstant);
for (int j = 0; j < mNumVar && r == MSK_RES_OK; ++j)
{
/* Set the linear term c_j in the objective .*/
if (r == MSK_RES_OK)
r = MSK_putcj(task, j, mc[j]);
/* Set the bounds on variable j.*/
if (r == MSK_RES_OK)
{
if (mbLowerBounded[j] && mbUpperBounded[j])
{
if (mlb[j] == mub[j])
r = MSK_putbound(task, MSK_ACC_VAR, j, MSK_BK_FX, mlb[j], mub[j]);
else
{
CHECK(mlb[j] < mub[j]);
r = MSK_putbound(task, MSK_ACC_VAR, j, MSK_BK_RA, mlb[j], mub[j]);
}
}
else if (mbLowerBounded[j])
{
r = MSK_putbound(task, MSK_ACC_VAR, j , MSK_BK_LO, mlb[j], +MSK_INFINITY);
}
else if (mbUpperBounded[j])
{
r = MSK_putbound(task, MSK_ACC_VAR, j, MSK_BK_UP, -MSK_INFINITY, mub[j]);
}
else
{
r = MSK_putbound(task, MSK_ACC_VAR, j, MSK_BK_FR, -MSK_INFINITY, +MSK_INFINITY);
}
}
/* Input column j of A */
if (r == MSK_RES_OK && mNumCon)
{
int currentColumnIdx = mAColumnStartIdx[j];
int nextColumnIdx = mAColumnStartIdx[j + 1];
if (nextColumnIdx - currentColumnIdx > 0)
r = MSK_putavec(task, MSK_ACC_VAR, j, nextColumnIdx - currentColumnIdx, &(mARowIdx[currentColumnIdx]), &(mAValues[currentColumnIdx]));
}
}
/* Set the bounds on constraints .
for i=1, ... , NUMCON : blc [i] <= constraint i <= buc [i] */
for (int i = 0; i < mNumCon && r == MSK_RES_OK; ++i)
{
if (mbConstraintLowerBounded[i] && mbConstraintUpperBounded[i])
{
if (mlbc[i] == mubc[i])
{
r = MSK_putbound(task, MSK_ACC_CON, i, MSK_BK_FX, mlbc[i], mubc[i]);
}
else
{
r = MSK_putbound(task, MSK_ACC_CON, i, MSK_BK_RA, mlbc[i], mubc[i]);
}
}
else if (mbConstraintLowerBounded[i])
{
r = MSK_putbound(task, MSK_ACC_CON, i, MSK_BK_LO, mlbc[i], +MSK_INFINITY);
}
else if (mbConstraintUpperBounded[i])
{
r = MSK_putbound(task, MSK_ACC_CON, i, MSK_BK_UP, -MSK_INFINITY, mubc[i]);
}
else
{
LOG(WARNING) << "Every constraint should not be free.";
}
}
for (int i = 0; i < mNumCone; ++i)
{
Cone& cone = mCones[i];
r = MSK_appendcone(task, MSK_CT_RQUAD, 0.0, cone.mSubscripts.size(), cone.GetMosekConeSubId());
//r = MSK_appendcone(task, MSK_CT_QUAD, 0.0, cone.mSubscripts.size(), cone.GetMosekConeSubId());
}
if (r == MSK_RES_OK)
{
MSKrescodee trmcode;
r = MSK_optimizetrm(task, &trmcode);
MSK_solutionsummary(task, MSK_STREAM_LOG);
if (r == MSK_RES_OK)
{
MSKsolstae solsta;
MSK_getsolutionstatus(task, MSK_SOL_ITR, NULL, &solsta);
double* result = new double[mNumVar];
switch (solsta)
{
case MSK_SOL_STA_OPTIMAL:
case MSK_SOL_STA_NEAR_OPTIMAL:
MSK_getsolutionslice(task, MSK_SOL_ITR, MSK_SOL_ITEM_XX, 0, mNumVar, result);
LOG(INFO) << "Optimal primal solution";
ret = true;
solution = VectorXd::Zero(mNumVar);
sol = VectorXd::Zero(mNumVar);
for (int k = 0; k < mNumVar; ++k)
{
solution[k] = result[k];
sol[k] = result[k];
}
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:
LOG(WARNING) << "Primal or dual infeasibility certificate found.";
break;
case MSK_SOL_STA_UNKNOWN:
LOG(WARNING) << "The status of the solution could not be determined.";
break;
default:
LOG(WARNING) << "Other solution status.";
break;
}
delete[] result;
}
}
else
{
LOG(WARNING) << "Error while optimizing.";
}
if (r != MSK_RES_OK)
{
char symname[MSK_MAX_STR_LEN];
char desc[MSK_MAX_STR_LEN];
LOG(WARNING) << "An error occurred while optimizing.";
MSK_getcodedesc(r, symname, desc);
LOG(WARNING) << "Error " << symname << " - " << desc;
}
}
MSK_deletetask(&task);
MSK_deleteenv(&env);
#endif
return ret;
}
int main(int argc,char *argv[])
{
MSKrescodee r;
MSKidxt i,j;
double c[] = {3.0, 1.0, 5.0, 1.0};
/* Below is the sparse representation of the A
matrix stored by column. */
MSKlidxt aptrb[] = {0, 2, 5, 7};
MSKlidxt aptre[] = {2, 5, 7, 9};
MSKidxt asub[] = { 0, 1,
0, 1, 2,
0, 1,
1, 2};
double aval[] = { 3.0, 2.0,
1.0, 1.0, 2.0,
2.0, 3.0,
1.0, 3.0};
/* Bounds on constraints. */
MSKboundkeye bkc[] = {MSK_BK_FX, MSK_BK_LO, MSK_BK_UP };
double blc[] = {30.0, 15.0, -MSK_INFINITY};
double buc[] = {30.0, +MSK_INFINITY, 25.0 };
/* Bounds on variables. */
MSKboundkeye bkx[] = {MSK_BK_LO, MSK_BK_RA, MSK_BK_LO, MSK_BK_LO };
double blx[] = {0.0, 0.0, 0.0, 0.0 };
double bux[] = {+MSK_INFINITY, 10.0, +MSK_INFINITY, +MSK_INFINITY };
double xx[NUMVAR];
MSKenv_t env = NULL;
MSKtask_t task = NULL;
/* Create the mosek environment. */
r = MSK_makeenv(&env,NULL,NULL,NULL,NULL);
/* Directs the env log stream to the 'printstr' function. */
if ( r==MSK_RES_OK )
MSK_linkfunctoenvstream(env,MSK_STREAM_LOG,NULL,printstr);
/* Initialize the environment. */
if ( r==MSK_RES_OK )
r = MSK_initenv(env);
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. */
if ( r==MSK_RES_OK )
MSK_linkfunctotaskstream(task,MSK_STREAM_LOG,NULL,printstr);
/* Give MOSEK an estimate of the size of the input data.
This is done to increase the speed of inputting data.
However, it is optional. */
if (r == MSK_RES_OK)
r = MSK_putmaxnumvar(task,NUMVAR);
if (r == MSK_RES_OK)
r = MSK_putmaxnumcon(task,NUMCON);
if (r == MSK_RES_OK)
r = MSK_putmaxnumanz(task,NUMANZ);
/* Append 'NUMCON' empty constraints.
The constraints will initially have no bounds. */
if ( r == MSK_RES_OK )
r = MSK_append(task,MSK_ACC_CON,NUMCON);
/* Append 'NUMVAR' variables.
The variables will initially be fixed at zero (x=0). */
if ( r == MSK_RES_OK )
r = MSK_append(task,MSK_ACC_VAR,NUMVAR);
/* Optionally add a constant term to the objective. */
if ( r ==MSK_RES_OK )
r = MSK_putcfix(task,0.0);
for(j=0; j<NUMVAR && r == MSK_RES_OK; ++j)
{
/* Set the linear term c_j in the objective.*/
if(r == MSK_RES_OK)
r = MSK_putcj(task,j,c[j]);
/* Set the bounds on variable j.
blx[j] <= x_j <= bux[j] */
if(r == MSK_RES_OK)
r = MSK_putbound(task,
MSK_ACC_VAR, /* Put bounds on variables.*/
j, /* Index of variable.*/
bkx[j], /* Bound key.*/
blx[j], /* Numerical value of lower bound.*/
bux[j]); /* Numerical value of upper bound.*/
/* Input column j of A */
if(r == MSK_RES_OK)
r = MSK_putavec(task,
MSK_ACC_VAR, /* Input columns of A.*/
j, /* Variable (column) index.*/
aptre[j]-aptrb[j], /* Number of non-zeros in column j.*/
asub+aptrb[j], /* Pointer to row indexes of column j.*/
aval+aptrb[j]); /* Pointer to Values of column j.*/
}
/* Set the bounds on constraints.
for i=1, ...,NUMCON : blc[i] <= constraint i <= buc[i] */
for(i=0; i<NUMCON && r==MSK_RES_OK; ++i)
r = MSK_putbound(task,
MSK_ACC_CON, /* Put bounds on constraints.*/
i, /* Index of constraint.*/
bkc[i], /* Bound key.*/
blc[i], /* Numerical value of lower bound.*/
buc[i]); /* Numerical value of upper bound.*/
/* Maximize objective function. */
if (r == MSK_RES_OK)
r = MSK_putobjsense(task,
MSK_OBJECTIVE_SENSE_MAXIMIZE);
if ( r==MSK_RES_OK )
{
MSKrescodee trmcode;
/* Run optimizer */
r = MSK_optimizetrm(task,&trmcode);
/* Print a summary containing information
about the solution for debugging purposes. */
MSK_solutionsummary (task,MSK_STREAM_LOG);
if ( r==MSK_RES_OK )
{
MSKsolstae solsta;
int j;
MSK_getsolutionstatus (task,
MSK_SOL_BAS,
NULL,
&solsta);
switch(solsta)
{
case MSK_SOL_STA_OPTIMAL:
case MSK_SOL_STA_NEAR_OPTIMAL:
MSK_getsolutionslice(task,
MSK_SOL_BAS, /* Request the basic solution. */
MSK_SOL_ITEM_XX,/* Which part of solution. */
0, /* Index of first variable. */
NUMVAR, /* Index of last variable+1. */
xx);
printf("Optimal primal solution\n");
for(j=0; j<NUMVAR; ++j)
printf("x[%d]: %e\n",j,xx[j]);
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:
printf("The status of the solution could not be determined.\n");
break;
default:
printf("Other solution status.");
break;
}
}
else
{
printf("Error while optimizing.\n");
}
}
if (r != MSK_RES_OK)
{
/* 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);
}
MSK_deletetask(&task);
MSK_deleteenv(&env);
}
return r;
}
void MyQCQP::optimize()
{
// resize alpha
if(alpha != NULL)
delete []alpha;
alpha = new double[numvar];
double *c_ = new double[numvar];
for(int i = 0;i<numvar;i++) c_[i] = c[i];
MSKboundkeye *bkc_ = new MSKboundkeye[numcon];
double * blc_ = new double[numcon];
double * buc_ = new double[numcon];
for(int i = 0;i<numcon;i++)
{
bkc_[i] = bkc[i];
blc_[i] = blc[i];
buc_[i] = buc[i];
}
MSKboundkeye *bkx_ = new MSKboundkeye[numvar];
double * blx_ = new double[numvar];
double * bux_ = new double[numvar];
for(int i = 0;i<numvar;i++)
{
bkx_[i] = bkx[i];
blx_[i] = blx[i];
bux_[i] = bux[i];
}
MSKlidxt *aptrb_ = new MSKlidxt[aptrb.size()];
for(size_t i = 0;i<aptrb.size();i++) aptrb_[i] = aptrb[i];
MSKlidxt * aptre_ = new MSKlidxt[aptre.size()];
for(size_t i = 0;i<aptre.size();i++) aptre_[i] = aptre[i];
MSKidxt * asub_ = new MSKidxt[asub.size()];
for(size_t i = 0;i<asub.size();i++) asub_[i] = asub[i];
double *aval_ = new double[aval.size()];
for(size_t i = 0;i<aval.size();i++) aval_[i] = aval[i];
MSKrescodee r;
MSKenv_t env;
MSKtask_t task;
r = MSK_makeenv(&env,NULL,NULL,NULL,NULL);
r = MSK_initenv(env);
if(r == MSK_RES_OK)
{
r = MSK_maketask(env,numcon,numvar,&task);
if(r == MSK_RES_OK)
r = MSK_append(task,MSK_ACC_CON,numcon);
if(r == MSK_RES_OK)
r = MSK_append(task,MSK_ACC_VAR, numvar);
for(int j = 0;j<numvar && r== MSK_RES_OK;j++)
{
if(r == MSK_RES_OK)
r = MSK_putcj(task,j,c_[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)
r = MSK_putavec(task,MSK_ACC_VAR,j,aptre_[j] - aptrb_[j], asub_ + aptrb_[j],aval_+aptrb_[j]);
}
for(int i=0;i<numcon && r== MSK_RES_OK;i++)
{
r = MSK_putbound(task,MSK_ACC_CON,i,bkc_[i],blc_[i],buc_[i]);
}
delete []c_;
delete []bkx_;
delete []blx_;
delete []bux_;
delete []aptrb_;
delete []aptre_;
delete []asub_;
delete []aval_;
delete []bkc_;
delete []blc_;
delete []buc_;
for(int i=0;i<numcon-1 && r== MSK_RES_OK;i++) // numcon-1 quadratic constraints
{
int nzero = qsubi[i].size();
MSKidxt * qsubi_ = new MSKidxt[nzero];
MSKidxt * qsubj_ = new MSKidxt[nzero];
double * qval_ = new double[nzero];
for(int m = 0;m<nzero;m++)
{
qsubi_[m] = qsubi[i][m];
qsubj_[m] = qsubj[i][m];
qval_[m] = qval[i][m];
}
if(r == MSK_RES_OK)
r = MSK_putqconk(task,i,nzero,qsubi_,qsubj_,qval_);
delete []qsubi_;
delete []qsubj_;
delete []qval_;
}
if(r == MSK_RES_OK)
r = MSK_putobjsense(task,MSK_OBJECTIVE_SENSE_MINIMIZE);
if(r == MSK_RES_OK)
{
MSKrescodee trmcode;
r = MSK_optimizetrm(task,&trmcode);
MSK_getsolutionslice(task,MSK_SOL_ITR, MSK_SOL_ITEM_XX,0,numvar,alpha);
MSK_getsolutionslice(task,MSK_SOL_ITR,MSK_SOL_ITEM_SUC,0,numcon,mu);
}
MSK_deletetask(&task);
}
MSK_deleteenv(&env);
}
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[])
{
MSKtask_t task = NULL;
MSKenv_t env = NULL;
MSKrescodee r = MSK_RES_OK;
if (argc <= 1)
{
printf ("Missing argument. The syntax is:\n");
printf (" simple inputfile [ solutionfile ]\n");
}
else
{
/* Create the mosek environment.
The `NULL' arguments here, are used to specify customized
memory allocators and a memory debug file. These can
safely be ignored for now. */
r = MSK_makeenv(&env, NULL, NULL, NULL, NULL);
/* Initialize the environment */
if ( r==MSK_RES_OK )
MSK_initenv (env);
/* Create a task object linked to the environment env.
Initially we create it with 0 variables and 0 columns,
since we do not know the size of the problem. */
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);
/* We assume that a problem file was given as the first command
line argument (received in `argv'). */
if ( r==MSK_RES_OK )
r = MSK_readdata (task, argv[1]);
/* Solve the problem */
if ( r==MSK_RES_OK )
{
MSKrescodee trmcode;
MSK_optimizetrm(task,&trmcode);
}
/* Print a summary of the solution. */
MSK_solutionsummary(task, MSK_STREAM_MSG);
if (r == MSK_RES_OK)
{
MSKprostae prosta;
MSKsolstae solsta;
MSKrealt primalobj,maxpbi,maxpcni,maxpeqi,maxinti,
dualobj, maxdbi, maxdcni, maxdeqi;
MSKintt isdef;
MSKsoltypee whichsol = MSK_SOL_BAS;
int accepted = 1;
MSK_getsolutioninf (
task,
whichsol,
&prosta,
&solsta,
&primalobj,
&maxpbi,
&maxpcni,
&maxpeqi,
&maxinti,
&dualobj,
&maxdbi,
&maxdcni,
&maxdeqi);
switch(solsta)
{
case MSK_SOL_STA_OPTIMAL:
case MSK_SOL_STA_NEAR_OPTIMAL:
{
double max_primal_infeas = 0.0; /* maximal primal infeasibility */
double max_dual_infeas = 0.0; /* maximal dual infeasibility */
double obj_gap = fabs(dualobj-primalobj);
max_primal_infeas = double_max(max_primal_infeas,maxpbi);
max_primal_infeas = double_max(max_primal_infeas,maxpcni);
max_primal_infeas = double_max(max_primal_infeas,maxpeqi);
max_dual_infeas = double_max(max_dual_infeas,maxdbi);
max_dual_infeas = double_max(max_dual_infeas,maxdcni);
max_dual_infeas = double_max(max_dual_infeas,maxdeqi);
/* Assume the application needs the solution to be within
1e-6 ofoptimality in an absolute sense. Another approach
would be looking at the relative objective gap */
printf("Objective gap: %e\n",obj_gap);
if (obj_gap > 1e-6)
{
printf("Warning: The objective gap is too large.");
accepted = 0;
}
printf("Max primal infeasibility: %e\n", max_primal_infeas);
printf("Max dual infeasibility: %e\n" , max_dual_infeas);
/* We will accept a primal infeasibility of 1e-8 and
dual infeasibility of 1e-6 */
if (max_primal_infeas > 1e-8)
{
printf("Warning: Primal infeasibility is too large");
accepted = 0;
}
if (max_dual_infeas > 1e-6)
{
printf("Warning: Dual infeasibility is too large");
accepted = 0;
}
}
if (accepted && r == MSK_RES_OK)
{
MSKintt numvar,j;
MSKrealt *xx = NULL;
MSK_getnumvar(task,&numvar);
xx = (double *) malloc(numvar*sizeof(MSKrealt));
MSK_getsolutionslice(task,
MSK_SOL_BAS, /* Request the basic solution. */
MSK_SOL_ITEM_XX,/* Which part of solution. */
0, /* Index of first variable. */
numvar, /* Index of last variable+1. */
xx);
printf("Optimal primal solution\n");
for(j=0; j<numvar; ++j)
printf("x[%d]: %e\n",j,xx[j]);
free(xx);
}
else
{
/* Print detailed information about the solution */
if (r == MSK_RES_OK)
r = MSK_analyzesolution(task,MSK_STREAM_LOG,whichsol);
}
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:
printf("The status of the solution could not be determined.\n");
break;
default:
printf("Other solution status");
break;
}
}
else
{
printf("Error while optimizing.\n");
}
MSK_deletetask(&task);
MSK_deleteenv(&env);
}
return r;
}
int mosek_qp_optimize(double** G, double* delta, double* alpha, long k, double C, double *dual_obj) {
long i,j,t;
double *c;
MSKlidxt *aptrb;
MSKlidxt *aptre;
MSKidxt *asub;
double *aval;
MSKboundkeye bkc[1];
double blc[1];
double buc[1];
MSKboundkeye *bkx;
double *blx;
double *bux;
MSKidxt *qsubi,*qsubj;
double *qval;
MSKenv_t env;
MSKtask_t task;
MSKrescodee r;
/*double dual_obj;*/
c = (double*) malloc(sizeof(double)*k);
assert(c!=NULL);
aptrb = (MSKlidxt*) malloc(sizeof(MSKlidxt)*k);
assert(aptrb!=NULL);
aptre = (MSKlidxt*) malloc(sizeof(MSKlidxt)*k);
assert(aptre!=NULL);
asub = (MSKidxt*) malloc(sizeof(MSKidxt)*k);
assert(asub!=NULL);
aval = (double*) malloc(sizeof(double)*k);
assert(aval!=NULL);
bkx = (MSKboundkeye*) malloc(sizeof(MSKboundkeye)*k);
assert(bkx!=NULL);
blx = (double*) malloc(sizeof(double)*k);
assert(blx!=NULL);
bux = (double*) malloc(sizeof(double)*k);
assert(bux!=NULL);
qsubi = (MSKidxt*) malloc(sizeof(MSKidxt)*(k*(k+1)/2));
assert(qsubi!=NULL);
qsubj = (MSKidxt*) malloc(sizeof(MSKidxt)*(k*(k+1)/2));
assert(qsubj!=NULL);
qval = (double*) malloc(sizeof(double)*(k*(k+1)/2));
assert(qval!=NULL);
/* DEBUG */
/*
for (i=0;i<k;i++) {
printf("delta: %.4f\n", delta[i]);
}
printf("G:\n");
for (i=0;i<k;i++) {
for (j=0;j<k;j++) {
printf("%.4f ", G[i][j]);
}
printf("\n");
}
fflush(stdout);
*/
/* DEBUG */
for (i=0;i<k;i++) {
c[i] = -delta[i];
aptrb[i] = i;
aptre[i] = i+1;
asub[i] = 0;
aval[i] = 1.0;
bkx[i] = MSK_BK_LO;
blx[i] = 0.0;
bux[i] = MSK_INFINITY;
}
bkc[0] = MSK_BK_UP;
blc[0] = -MSK_INFINITY;
buc[0] = C;
/*
bkc[0] = MSK_BK_FX;
blc[0] = C;
buc[0] = C;
*/
/* create mosek environment */
r = MSK_makeenv(&env, NULL, NULL, NULL, NULL);
/* check return code */
if (r==MSK_RES_OK) {
/* directs output to printstr function */
MSK_linkfunctoenvstream(env, MSK_STREAM_LOG, NULL, printstr);
}
/* initialize the environment */
r = MSK_initenv(env);
if (r==MSK_RES_OK) {
/* create the optimization task */
r = MSK_maketask(env,1,k,&task);
if (r==MSK_RES_OK) {
r = MSK_linkfunctotaskstream(task, MSK_STREAM_LOG,NULL,printstr);
if (r==MSK_RES_OK) {
r = MSK_inputdata(task,
1,k,
1,k,
c,0.0,
aptrb,aptre,
asub,aval,
bkc,blc,buc,
bkx,blx,bux);
}
if (r==MSK_RES_OK) {
/* coefficients for the Gram matrix */
t = 0;
for (i=0;i<k;i++) {
for (j=0;j<=i;j++) {
qsubi[t] = i;
qsubj[t] = j;
qval[t] = G[i][j];
t++;
}
}
r = MSK_putqobj(task, k*(k+1)/2, qsubi,qsubj,qval);
}
/* DEBUG */
/*
printf("t: %ld\n", t);
for (i=0;i<t;i++) {
printf("qsubi: %d, qsubj: %d, qval: %.4f\n", qsubi[i], qsubj[i], qval[i]);
}
fflush(stdout);
*/
/* DEBUG */
/* set relative tolerance gap (DEFAULT = 1E-8)*/
//MSK_putdouparam(task, MSK_DPAR_INTPNT_TOL_REL_GAP, 1E-10);
MSK_putdouparam(task, MSK_DPAR_INTPNT_TOL_REL_GAP, 1E-14);
if (r==MSK_RES_OK) {
r = MSK_optimize(task);
}
if (r==MSK_RES_OK) {
MSK_getsolutionslice(task,
MSK_SOL_ITR,
MSK_SOL_ITEM_XX,
0,
k,
alpha);
/* print out alphas */
/*
for (i=0;i<k;i++) {
printf("alpha[%ld]: %.8f\n", i, alpha[i]); fflush(stdout);
}
*/
/* output the objective value */
MSK_getprimalobj(task, MSK_SOL_ITR, dual_obj);
//printf("ITER DUAL_OBJ %.8g\n", -(*dual_obj)); fflush(stdout);
}
MSK_deletetask(&task);
}
MSK_deleteenv(&env);
}
/* free the memory */
free(c);
free(aptrb);
free(aptre);
free(asub);
free(aval);
free(bkx);
free(blx);
free(bux);
free(qsubi);
free(qsubj);
free(qval);
if(r == MSK_RES_OK)
return(0);
else
return(r);
}
