// Test KKT conditions on the solution.
// The function returns true if the tested KKT conditions are satisfied
// and false otherwise.
// The function assumes that the model currently extracted to CPLEX is fully
// described by obj, vars and rngs.
static bool
checkkkt (IloCplex& cplex, IloObjective const& obj, IloNumVarArray const& vars,
IloRangeArray const& rngs, IloIntArray const& cone, double tol)
{
IloEnv env = cplex.getEnv();
IloModel model = cplex.getModel();
IloNumArray x(env), dslack(env);
IloNumArray pi(env, rngs.getSize()), slack(env);
// Read primal and dual solution information.
cplex.getValues(x, vars);
cplex.getSlacks(slack, rngs);
// pi for second order cone constraints.
getsocpconstrmultipliers(cplex, vars, rngs, pi, dslack);
// pi for linear constraints.
for (IloInt i = 0; i < rngs.getSize(); ++i) {
IloRange r = rngs[i];
if ( !r.getQuadIterator().ok() )
pi[idx(r)] = cplex.getDual(r);
}
// Print out the data we just fetched.
streamsize oprec = env.out().precision(3);
ios_base::fmtflags oflags = env.out().setf(ios::fixed | ios::showpos);
env.out() << "x = [";
for (IloInt i = 0; i < x.getSize(); ++i)
env.out() << " " << x[i];
env.out() << " ]" << endl;
env.out() << "dslack = [";
for (IloInt i = 0; i < dslack.getSize(); ++i)
env.out() << " " << dslack[i];
env.out() << " ]" << endl;
env.out() << "pi = [";
for (IloInt i = 0; i < rngs.getSize(); ++i)
env.out() << " " << pi[i];
env.out() << " ]" << endl;
env.out() << "slack = [";
for (IloInt i = 0; i < rngs.getSize(); ++i)
env.out() << " " << slack[i];
env.out() << " ]" << endl;
env.out().precision(oprec);
env.out().flags(oflags);
// Test 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.
// 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,
// - the dslack value for all non-cone variables must be non-negative.
// Note that we do not support ranged constraints here.
for (IloInt i = 0; i < vars.getSize(); ++i) {
IloNumVar v = vars[i];
if ( cone[i] == NOT_IN_CONE && dslack[i] < -tol ) {
env.error() << "Dual multiplier for " << v << " is not feasible: "
<< dslack[i] << endl;
return false;
}
}
for (IloInt i = 0; i < rngs.getSize(); ++i) {
IloRange r = rngs[i];
if ( fabs (r.getLB() - r.getUB()) <= tol ) {
// Nothing to check for equality constraints.
}
else if ( r.getLB() > -IloInfinity && pi[i] > tol ) {
env.error() << "Dual multiplier " << pi[i] << " for >= constraint"
<< endl << r << endl
<< "not feasible"
<< endl;
return false;
}
else if ( r.getUB() < IloInfinity && pi[i] < -tol ) {
env.error() << "Dual multiplier " << pi[i] << " for <= constraint"
<< endl << r << endl
<< "not feasible"
<< endl;
return false;
}
}
// Test complementary slackness.
// For each constraint either the constraint must have zero slack or
// the dual multiplier for the constraint must be 0. We must also
// consider the special case in which a variable is not explicitly
// contained in a second order cone constraint.
for (IloInt i = 0; i < vars.getSize(); ++i) {
if ( cone[i] == NOT_IN_CONE ) {
if ( fabs(x[i]) > tol && dslack[i] > tol ) {
env.error() << "Invalid complementary slackness for " << vars[i]
<< ":" << endl
<< " " << x[i] << " and " << dslack[i]
<< endl;
return false;
}
}
}
for (IloInt i = 0; i < rngs.getSize(); ++i) {
if ( fabs(slack[i]) > tol && fabs(pi[i]) > tol ) {
env.error() << "Invalid complementary slackness for "
<< endl << rngs[i] << ":" << endl
<< " " << slack[i] << " and " << pi[i]
<< endl;
return false;
}
}
// 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.
IloNumArray sum(env, vars.getSize());
for (IloExpr::LinearIterator it = obj.getLinearIterator(); it.ok(); ++it)
sum[idx(it.getVar())] = it.getCoef();
for (IloInt i = 0; i < vars.getSize(); ++i) {
IloNumVar v = vars[i];
if ( cone[i] == NOT_IN_CONE )
sum[i] -= dslack[i];
}
for (IloInt i = 0; i < rngs.getSize(); ++i) {
IloRange r = rngs[i];
if ( r.getQuadIterator().ok() ) {
// Quadratic (second order cone) constraint.
IloNum norm = 0.0;
for (IloExpr::QuadIterator q = r.getQuadIterator(); q.ok(); ++q) {
if ( q.getCoef() > 0 )
norm += x[idx(q.getVar1())] * x[idx(q.getVar1())];
}
norm = sqrt(norm);
if ( fabs(norm) <= tol ) {
// Derivative is not defined. Skip test.
env.warning() << "Cannot test stationarity at non-differentiable point."
<< endl;
return true;
}
else {
for (IloExpr::QuadIterator q = r.getQuadIterator(); q.ok(); ++q) {
if ( q.getCoef() < 0 )
sum[idx(q.getVar1())] -= pi[i];
else
sum[idx(q.getVar1())] += pi[i] * x[idx(q.getVar1())] / norm;
}
}
}
else {
// Linear constraint.
for (IloExpr::LinearIterator l = r.getLinearIterator(); l.ok(); ++l)
sum[idx(l.getVar())] -= pi[i] * l.getCoef();
}
}
// Now test that all elements in sum[] are 0.
for (IloInt i = 0; i < vars.getSize(); ++i) {
if ( fabs(sum[i]) > tol ) {
env.error() << "Invalid stationarity " << sum[i] << " for "
<< vars[i] << endl;
return false;
}
}
return true;
}
/*
* 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;
}