/*
* The function returns a true value if the tested KKT conditions are
* satisfied and false otherwise.
*/
static int
checkkkt (CPXCENVptr env, CPXLPptr lp, int const *cone, double tol)
{
int cols = CPXgetnumcols (env, lp);
int rows = CPXgetnumrows (env, lp);
int qcons = CPXgetnumqconstrs (env, lp);
double *dslack = NULL, *pi = NULL, *socppi = NULL;
double *val = NULL, *rhs = NULL;
int *ind = NULL;
char *sense = NULL;
double *x = NULL, *slack = NULL, *qslack = NULL;
double *sum = NULL;
qbuf_type qbuf;
CPXCHANNELptr resc, warnc, errc, logc;
int ok = 0, skip = 0;
int status;
int i, j, q;
qbuf_init (&qbuf);
/* Get the channels on which we may report. */
if ( (status = CPXgetchannels (env, &resc, &warnc, &errc, &logc)) != 0 )
goto TERMINATE;
/* Fetch results and problem data that we need to check the KKT
* conditions.
*/
CPXmsg (logc, "Fetching results ... ");
if ( (cols > 0 && (dslack = malloc (cols * sizeof (*dslack))) == NULL) ||
(rows > 0 && (pi = malloc (rows * sizeof (*pi))) == NULL) ||
(qcons > 0 && (socppi = malloc (qcons * sizeof (*socppi))) == NULL) ||
(cols > 0 && (x = malloc (cols * sizeof (*x))) == NULL) ||
(rows > 0 && (sense = malloc (rows * sizeof (*sense))) == NULL ) ||
(rows > 0 && (slack = malloc (rows * sizeof (*slack))) == NULL ) ||
(qcons > 0 && (qslack = malloc (qcons * sizeof (*qslack))) == NULL) ||
(cols > 0 && (sum = malloc (cols * sizeof (*sum))) == NULL) ||
(cols > 0 && (val = malloc (cols * sizeof (*val))) == NULL) ||
(cols > 0 && (ind = malloc (cols * sizeof (*ind))) == NULL) ||
(rows > 0 && (rhs = malloc (rows * sizeof (*rhs))) == NULL) )
{
CPXmsg (errc, "Out of memory!\n");
goto TERMINATE;
}
/* Fetch problem data. */
if ( (status = CPXgetsense (env, lp, sense, 0, rows - 1)) != 0 )
goto TERMINATE;
if ( (status = CPXgetrhs (env, lp, rhs, 0, rows - 1)) != 0 )
goto TERMINATE;
/* Fetch solution information. */
if ( (status = CPXgetx (env, lp, x, 0, cols - 1)) != 0 )
goto TERMINATE;
if ( (status = CPXgetpi (env, lp, pi, 0, rows - 1)) != 0 )
goto TERMINATE;
if ( (status = getsocpconstrmultipliers (env, lp, dslack, socppi)) != 0 )
goto TERMINATE;
if ( (status = CPXgetslack (env, lp, slack, 0, rows - 1)) != 0 )
goto TERMINATE;
if ( (status = CPXgetqconstrslack (env, lp, qslack, 0, qcons - 1)) != 0 )
goto TERMINATE;
CPXmsg (logc, "ok.\n");
/* Print out the solution data we just fetched. */
CPXmsg (resc, "x = [");
for (j = 0; j < cols; ++j)
CPXmsg (resc, " %+7.3f", x[j]);
CPXmsg (resc, " ]\n");
CPXmsg (resc, "dslack = [");
for (j = 0; j < cols; ++j)
CPXmsg (resc, " %+7.3f", dslack[j]);
CPXmsg (resc, " ]\n");
CPXmsg (resc, "pi = [");
for (i = 0; i < rows; ++i)
CPXmsg (resc, " %+7.3f", pi[i]);
CPXmsg (resc, " ]\n");
CPXmsg (resc, "slack = [");
for (i = 0; i < rows; ++i)
CPXmsg (resc, " %+7.3f", slack[i]);
CPXmsg (resc, " ]\n");
CPXmsg (resc, "socppi = [");
for (q = 0; q < qcons; ++q)
CPXmsg (resc, " %+7.3f", socppi[q]);
CPXmsg (resc, " ]\n");
CPXmsg (resc, "qslack = [");
for (q = 0; q < qcons; ++q)
CPXmsg (resc, " %+7.3f", qslack[q]);
CPXmsg (resc, " ]\n");
/* Test primal feasibility. */
CPXmsg (logc, "Testing primal feasibility ... ");
/* This example illustrates the use of dual vectors returned by CPLEX
* to verify dual feasibility, so we do not test primal feasibility
* here. */
CPXmsg (logc, "ok.\n");
/* Test dual feasibility.
* We must have
* - for all <= constraints the respective pi value is non-negative,
* - for all >= constraints the respective pi value is non-positive,
* - since all quadratic constraints are <= constraints the socppi
* value must be non-negative for all quadratic constraints,
* - the dslack value for all non-cone variables must be non-negative.
* Note that we do not support ranged constraints here.
*/
CPXmsg (logc, "Testing dual feasibility ... ");
for (i = 0; i < rows; ++i) {
switch (sense[i]) {
case 'L':
if ( pi[i] < -tol ) {
CPXmsg (errc, "<= row %d has invalid dual multiplier %f.\n",
i, pi[i]);
goto TERMINATE;
}
break;
case 'G':
if ( pi[i] > tol ) {
CPXmsg (errc, ">= row %d has invalid dual multiplier %f.\n",
i, pi[i]);
goto TERMINATE;
}
break;
case 'E':
/* Nothing to check here. */
break;
}
}
for (q = 0; q < qcons; ++q) {
if ( socppi[q] < -tol ) {
CPXmsg (errc, "Quadratic constraint %d has invalid dual multiplier %f.\n",
q, socppi[q]);
goto TERMINATE;
}
}
for (j = 0; j < cols; ++j) {
if ( cone[j] == NOT_IN_CONE && dslack[j] < -tol ) {
CPXmsg (errc, "dslack value for column %d is invalid: %f\n", j, dslack[j]);
goto TERMINATE;
}
}
CPXmsg (logc, "ok.\n");
/* Test complementary slackness.
* For each constraint either the constraint must have zero slack or
* the dual multiplier for the constraint must be 0. Again, we must
* consider the special case in which a variable is not explicitly
* contained in a second order cone constraint (conestat[j] == 0).
*/
CPXmsg (logc, "Testing complementary slackness ... ");
for (i = 0; i < rows; ++i) {
if ( fabs (slack[i]) > tol && fabs (pi[i]) > tol ) {
CPXmsg (errc, "Complementary slackness not satisfied for row %d (%f, %f)\n",
i, slack[i], pi[i]);
goto TERMINATE;
}
}
for (q = 0; q < qcons; ++q) {
if ( fabs (qslack[q]) > tol && fabs (socppi[q]) > tol ) {
CPXmsg (errc, "Complementary slackness not satisfied for cone %d (%f, %f).\n",
q, qslack[q], socppi[q]);
goto TERMINATE;
}
}
for (j = 0; j < cols; ++j) {
if ( cone[j] == NOT_IN_CONE ) {
if ( fabs (x[j]) > tol && fabs (dslack[j]) > tol ) {
CPXmsg (errc, "Complementary slackness not satisfied for non-cone variable %f (%f, %f).\n",
j, x[j], dslack[j]);
goto TERMINATE;
}
}
}
CPXmsg (logc, "ok.\n");
/* Test stationarity.
* We must have
* c - g[i]'(X)*pi[i] = 0
* where c is the objective function, g[i] is the i-th constraint of the
* problem, g[i]'(x) is the derivate of g[i] with respect to x and X is the
* optimal solution.
* We need to distinguish the following cases:
* - linear constraints g(x) = ax - b. The derivative of such a
* constraint is g'(x) = a.
* - second order constraints g(x[1],...,x[n]) = -x[1] + |(x[2],...,x[n])|
* the derivative of such a constraint is
* g'(x) = (-1, x[2]/|(x[2],...,x[n])|, ..., x[n]/|(x[2],...,x[n])|
* (here |.| denotes the Euclidean norm).
* - bound constraints g(x) = -x for variables that are not explicitly
* contained in any second order cone constraint. The derivative for
* such a constraint is g'(x) = -1.
* Note that it may happen that the derivative of a second order cone
* constraint is not defined at the optimal solution X (this happens if
* X=0). In this case we just skip the stationarity test.
*/
CPXmsg (logc, "Testing stationarity ... ");
/* Initialize sum = c. */
if ( (status = CPXgetobj (env, lp, sum, 0, cols - 1)) != 0 )
goto TERMINATE;
/* Handle linear constraints. */
for (i = 0; i < rows; ++i) {
int nz, surplus, beg;
int n;
status = CPXgetrows (env, lp, &nz, &beg, ind, val, cols, &surplus,
i, i);
if ( status != 0 )
goto TERMINATE;
for (n = 0; n < nz; ++n) {
sum[ind[n]] -= pi[i] * val[n];
}
}
/* Handle second order cone constraints. */
for (q = 0; q < qcons; ++q) {
double norm = 0.0;
int n;
if ( !getqconstr (env, lp, q, &qbuf) )
goto TERMINATE;
for (n = 0; n < qbuf.qnz; ++n) {
if ( qbuf.qval[n] > 0 )
norm += x[qbuf.qcol[n]] * x[qbuf.qcol[n]];
}
norm = sqrt (norm);
if ( fabs (norm) <= tol ) {
CPXmsg (warnc, "WARNING: Cannot test stationarity at non-differentiable point.\n");
skip = 1;
break;
}
for (n = 0; n < qbuf.qnz; ++n) {
if ( qbuf.qval[n] < 0 )
sum[qbuf.qcol[n]] -= socppi[q];
else
sum[qbuf.qcol[n]] += socppi[q] * x[qbuf.qcol[n]] / norm;
}
}
/* Handle variables that do not appear in any second order cone constraint.
*/
for (j = 0; !skip && j < cols; ++j) {
if ( cone[j] == NOT_IN_CONE ) {
sum[j] -= dslack[j];
}
}
/* Now test that all the entries in sum[] are 0.
*/
for (j = 0; !skip && j < cols; ++j) {
if ( fabs (sum[j]) > tol ) {
CPXmsg (errc, "Stationarity not satisfied at index %d: %f\n",
j, sum[j]);
goto TERMINATE;
}
}
CPXmsg (logc, "ok.\n");
CPXmsg (logc, "KKT conditions are satisfied.\n");
ok = 1;
TERMINATE:
if ( !ok )
CPXmsg (logc, "failed.\n");
qbuf_clear (&qbuf);
free (rhs);
free (ind);
free (val);
free (sum);
free (qslack);
free (slack);
free (sense);
free (x);
free (socppi);
free (pi);
free (dslack);
return ok;
}
int
main (void)
{
int status, solstat;
CPXENVptr env;
CPXLPptr lp;
int i;
double x[NUMCOLS];
double cpi[NUMCOLS];
double rpi[NUMROWS];
double qpi[NUMQS];
double slack[NUMROWS], qslack[NUMQS];
double kktsum[NUMCOLS];
/* ********************************************************************** *
* *
* S E T U P P R O B L E M *
* *
* ********************************************************************** */
/* Create CPLEX environment and enable screen output.
*/
env = CPXopenCPLEX (&status);
if ( status != 0 )
goto TERMINATE;
status = CPXsetintparam (env, CPXPARAM_ScreenOutput, CPX_ON);
if ( status != 0 )
goto TERMINATE;
/* Create the problem object and populate it.
*/
lp = CPXcreateprob (env, &status, "qcpdual");
if ( status != 0 )
goto TERMINATE;
status = CPXnewcols (env, lp, NUMCOLS, obj, lb, ub, NULL, cname);
if ( status != 0 )
goto TERMINATE;
status = CPXaddrows (env, lp, 0, NUMROWS, NUMNZS, rhs, sense,
rmatbeg, rmatind, rmatval, NULL, rname);
if ( status != 0 )
goto TERMINATE;
for (i = 0; i < NUMQS; ++i) {
int const linend = (i == NUMQS - 1) ? NUMLINNZ : linbeg[i + 1];
int const quadend = (i == NUMQS - 1) ? NUMQUADNZ : quadbeg[i + 1];
status = CPXaddqconstr (env, lp, linend - linbeg[i],
quadend - quadbeg[i], qrhs[i], qsense[i],
&linind[linbeg[i]], &linval[linbeg[i]],
&quadrow[quadbeg[i]], &quadcol[quadbeg[i]],
&quadval[quadbeg[i]], qname[i]);
if ( status != 0 )
goto TERMINATE;
}
/* ********************************************************************** *
* *
* O P T I M I Z E P R O B L E M *
* *
* ********************************************************************** */
status = CPXsetdblparam (env, CPXPARAM_Barrier_QCPConvergeTol, 1e-10);
if ( status != 0 )
goto TERMINATE;
/* Solve the problem.
*/
status = CPXbaropt (env, lp);
if ( status != 0 )
goto TERMINATE;
solstat = CPXgetstat (env, lp);
if ( solstat != CPX_STAT_OPTIMAL ) {
fprintf (stderr, "No optimal solution found!\n");
goto TERMINATE;
}
/* ********************************************************************** *
* *
* Q U E R Y S O L U T I O N *
* *
* ********************************************************************** */
/* Optimal solution and slacks for linear and quadratic constraints. */
status = CPXgetx (env, lp, x, 0, NUMCOLS - 1);
if ( status != 0 )
goto TERMINATE;
status = CPXgetslack (env, lp, slack, 0, NUMROWS - 1);
if ( status != 0 )
goto TERMINATE;
status = CPXgetqconstrslack (env, lp, qslack, 0, NUMQS - 1);
if ( status != 0 )
goto TERMINATE;
/* Dual multipliers for linear constraints and bound constraints. */
status = CPXgetdj (env, lp, cpi, 0, NUMCOLS - 1);
if ( status != 0 )
goto TERMINATE;
status = CPXgetpi (env, lp, rpi, 0, NUMROWS - 1);
if ( status != 0 )
goto TERMINATE;
status = getqconstrmultipliers (env, lp, x, qpi, ZEROTOL);
if ( status != 0 )
goto TERMINATE;
/* ********************************************************************** *
* *
* C H E C K K K T C O N D I T I O N S *
* *
* Here we verify that the optimal solution computed by CPLEX (and *
* the qpi[] values computed above) satisfy the KKT conditions. *
* *
* ********************************************************************** */
/* Primal feasibility: This example is about duals so we skip this test. */
/* Dual feasibility: We must verify
* - for <= constraints (linear or quadratic) the dual
* multiplier is non-positive.
* - for >= constraints (linear or quadratic) the dual
* multiplier is non-negative.
*/
for (i = 0; i < NUMROWS; ++i) {
switch (sense[i]) {
case 'E': /* nothing */ break;
case 'R': /* nothing */ break;
case 'L':
if ( rpi[i] > ZEROTOL ) {
fprintf (stderr,
"Dual feasibility test failed for <= row %d: %f\n",
i, rpi[i]);
status = -1;
goto TERMINATE;
}
break;
case 'G':
if ( rpi[i] < -ZEROTOL ) {
fprintf (stderr,
"Dual feasibility test failed for >= row %d: %f\n",
i, rpi[i]);
status = -1;
goto TERMINATE;
}
break;
}
}
for (i = 0; i < NUMQS; ++i) {
switch (qsense[i]) {
case 'E': /* nothing */ break;
case 'L':
if ( qpi[i] > ZEROTOL ) {
fprintf (stderr,
"Dual feasibility test failed for <= quad %d: %f\n",
i, qpi[i]);
status = -1;
goto TERMINATE;
}
break;
case 'G':
if ( qpi[i] < -ZEROTOL ) {
fprintf (stderr,
"Dual feasibility test failed for >= quad %d: %f\n",
i, qpi[i]);
status = -1;
goto TERMINATE;
}
break;
}
}
/* Complementary slackness.
* For any constraint the product of primal slack and dual multiplier
* must be 0.
*/
for (i = 0; i < NUMROWS; ++i) {
if ( sense[i] != 'E' && fabs (slack[i] * rpi[i]) > ZEROTOL ) {
fprintf (stderr,
"Complementary slackness test failed for row %d: %f\n",
i, fabs (slack[i] * rpi[i]));
status = -1;
goto TERMINATE;
}
}
for (i = 0; i < NUMQS; ++i) {
if ( qsense[i] != 'E' && fabs (qslack[i] * qpi[i]) > ZEROTOL ) {
fprintf (stderr,
"Complementary slackness test failed for quad %d: %f\n",
i, fabs (qslack[i] * qpi[i]));
status = -1;
goto TERMINATE;
}
}
for (i = 0; i < NUMCOLS; ++i) {
if ( ub[i] < CPX_INFBOUND ) {
double const slk = ub[i] - x[i];
double const dual = cpi[i] < -ZEROTOL ? cpi[i] : 0.0;
if ( fabs (slk * dual) > ZEROTOL ) {
fprintf (stderr,
"Complementary slackness test failed for ub %d: %f\n",
i, fabs (slk * dual));
status = -1;
goto TERMINATE;
}
}
if ( lb[i] > -CPX_INFBOUND ) {
double const slk = x[i] - lb[i];
double const dual = cpi[i] > ZEROTOL ? cpi[i] : 0.0;
if ( fabs (slk * dual) > ZEROTOL ) {
printf ("lb=%f, x=%f, cpi=%f\n", lb[i], x[i], cpi[i]);
fprintf (stderr,
"Complementary slackness test failed for lb %d: %f\n",
i, fabs (slk * dual));
status = -1;
goto TERMINATE;
}
}
}
/* Stationarity.
* The difference between objective function and gradient at optimal
* solution multiplied by dual multipliers must be 0, i.e., for the
* optimal solution x
* 0 == c
* - sum(r in rows) r'(x)*rpi[r]
* - sum(q in quads) q'(x)*qpi[q]
* - sum(c in cols) b'(x)*cpi[c]
* where r' and q' are the derivatives of a row or quadratic constraint,
* x is the optimal solution and rpi[r] and qpi[q] are the dual
* multipliers for row r and quadratic constraint q.
* b' is the derivative of a bound constraint and cpi[c] the dual bound
* multiplier for column c.
*/
/* Objective function. */
for (i = 0; i < NUMCOLS; ++i)
kktsum[i] = obj[i];
/* Linear constraints.
* The derivative of a linear constraint ax - b (<)= 0 is just a.
*/
for (i = 0; i < NUMROWS; ++i) {
int const end = (i == NUMROWS - 1) ? NUMNZS : rmatbeg[i + 1];
int k;
for (k = rmatbeg[i]; k < end; ++k)
kktsum[rmatind[k]] -= rpi[i] * rmatval[k];
}
/* Quadratic constraints.
* The derivative of a constraint xQx + ax - b <= 0 is
* Qx + Q'x + a.
*/
for (i = 0; i < NUMQS; ++i) {
int j;
int k;
for (j = linbeg[i]; j < linbeg[i] + linnzcnt[i]; ++j)
kktsum[linind[j]] -= qpi[i] * linval[j];
for (k = quadbeg[i]; k < quadbeg[i] + quadnzcnt[i]; ++k) {
kktsum[quadrow[k]] -= qpi[i] * x[quadcol[k]] * quadval[k];
kktsum[quadcol[k]] -= qpi[i] * x[quadrow[k]] * quadval[k];
}
}
/* Bounds.
* The derivative for lower bounds is -1 and that for upper bounds
* is 1.
* CPLEX already returns dj with the appropriate sign so there is
* no need to distinguish between different bound types here.
*/
for (i = 0; i < NUMCOLS; ++i) {
kktsum[i] -= cpi[i];
}
for (i = 0; i < NUMCOLS; ++i) {
if ( fabs (kktsum[i]) > ZEROTOL ) {
fprintf (stderr, "Stationarity test failed at index %d: %f\n",
i, kktsum[i]);
status = -1;
goto TERMINATE;
}
}
/* KKT conditions satisfied. Dump out the optimal solutions and
* the dual values.
*/
printf ("Optimal solution satisfies KKT conditions.\n");
printf (" x[] =");
for (i = 0; i < NUMCOLS; ++i)
printf (" %7.3f", x[i]);
printf ("\n");
printf ("cpi[] =");
for (i = 0; i < NUMCOLS; ++i)
printf (" %7.3f", cpi[i]);
printf ("\n");
printf ("rpi[] =");
for (i = 0; i < NUMROWS; ++i)
printf (" %7.3f", rpi[i]);
printf ("\n");
printf ("qpi[] =");
for (i = 0; i < NUMQS; ++i)
printf (" %7.3f", qpi[i]);
printf ("\n");
TERMINATE:
/* ********************************************************************** *
* *
* C L E A N U P *
* *
* ********************************************************************** */
status = CPXfreeprob (env, &lp);
if ( status != 0 ) {
fprintf (stderr, "WARNING: Failed to free problem: %d\n", status);
}
status = CPXcloseCPLEX (&env);
if ( status != 0 ) {
fprintf (stderr, "WARNING: Failed to close CPLEX: %d\n", status);
}
return status;
}