int setCplexParam(IloCplex& cplex, IloEnv& env, int time_limit){
//Set cplex parameter
cplex.setParam(IloCplex::TiLim, time_limit);
cplex.setParam(IloCplex::Threads, 2);
cplex.setOut(env.getNullStream());
cplex.setParam(IloCplex::PreLinear, 0);
return 0;
}
// This routine set up the IloCplex algorithm to solve the worker LP, and
// creates the worker LP (i.e., the dual of flow constraints and
// capacity constraints of the flow MILP)
//
// Modeling variables:
// forall k in V0, i in V:
// u(k,i) = dual variable associated with flow constraint (k,i)
//
// forall k in V0, forall (i,j) in A:
// v(k,i,j) = dual variable associated with capacity constraint (k,i,j)
//
// Objective:
// minimize sum(k in V0) sum((i,j) in A) x(i,j) * v(k,i,j)
// - sum(k in V0) u(k,0) + sum(k in V0) u(k,k)
//
// Constraints:
// forall k in V0, forall (i,j) in A: u(k,i) - u(k,j) <= v(k,i,j)
//
// Nonnegativity on variables v(k,i,j)
// forall k in V0, forall (i,j) in A: v(k,i,j) >= 0
//
void
createWorkerLP(IloCplex cplex, IloNumVarArray v, IloNumVarArray u,
IloObjective obj, IloInt numNodes)
{
IloInt i, j, k;
IloEnv env = cplex.getEnv();
IloModel mod(env, "atsp_worker");
// Set up IloCplex algorithm to solve the worker LP
cplex.extract(mod);
cplex.setOut(env.getNullStream());
// Turn off the presolve reductions and set the CPLEX optimizer
// to solve the worker LP with primal simplex method.
cplex.setParam(IloCplex::Reduce, 0);
cplex.setParam(IloCplex::RootAlg, IloCplex::Primal);
// Create variables v(k,i,j) forall k in V0, (i,j) in A
// For simplicity, also dummy variables v(k,i,i) are created.
// Those variables are fixed to 0 and do not partecipate to
// the constraints.
IloInt numArcs = numNodes * numNodes;
IloInt vNumVars = (numNodes-1) * numArcs;
IloNumVarArray vTemp(env, vNumVars, 0, IloInfinity);
for (k = 1; k < numNodes; ++k) {
for (i = 0; i < numNodes; ++i) {
vTemp[(k-1)*numArcs + i *numNodes + i].setBounds(0, 0);
}
}
v.clear();
v.add(vTemp);
vTemp.end();
mod.add(v);
// Set names for variables v(k,i,j)
for (k = 1; k < numNodes; ++k) {
for(i = 0; i < numNodes; ++i) {
for(j = 0; j < numNodes; ++j) {
char varName[100];
sprintf(varName, "v.%d.%d.%d", (int) k, (int) i, (int) j);
v[(k-1)*numArcs + i*numNodes + j].setName(varName);
}
}
}
// Associate indices to variables v(k,i,j)
IloIntArray vIndex(env, vNumVars);
for (j = 0; j < vNumVars; ++j)
{
vIndex[j] = j;
v[j].setObject(&vIndex[j]);
}
// Create variables u(k,i) forall k in V0, i in V
IloInt uNumVars = (numNodes-1) * numNodes;
IloNumVarArray uTemp(env, uNumVars, -IloInfinity, IloInfinity);
u.clear();
u.add(uTemp);
uTemp.end();
mod.add(u);
// Set names for variables u(k,i)
for (k = 1; k < numNodes; ++k) {
for(i = 0; i < numNodes; ++i) {
char varName[100];
sprintf(varName, "u.%d.%d", (int) k, (int) i);
u[(k-1)*numNodes + i].setName(varName);
}
}
// Associate indices to variables u(k,i)
IloIntArray uIndex(env, uNumVars);
for (j = 0; j < uNumVars; ++j)
{
uIndex[j] = vNumVars + j;
u[j].setObject(&uIndex[j]);
}
// Initial objective function is empty
obj.setSense(IloObjective::Minimize);
mod.add(obj);
// Add constraints:
// forall k in V0, forall (i,j) in A: u(k,i) - u(k,j) <= v(k,i,j)
for (k = 1; k < numNodes; ++k) {
for(i = 0; i < numNodes; ++i) {
for(j = 0; j < numNodes; ++j) {
if ( i != j ) {
IloExpr expr(env);
expr -= v[(k-1)*numArcs + i*(numNodes) + j];
expr += u[(k-1)*numNodes + i];
expr -= u[(k-1)*numNodes + j];
mod.add(expr <= 0);
expr.end();
}
}
}
}
}// END createWorkerLP
/** Create a new worker.
* The constructor mainly does the following:
* - create an IloCplex instance that refers to a remote worker,
* - load the model in <code>modelfile</code>,
* - setup parameters depending on this worker's index,
* - start an asynchronous solve.
* If anything fails then an exception will be thrown.
* @param env The environment used for instantiating Ilo* objects.
* @param i The index of the worker to be created. This also
* determines the parameter settings to use in this worker.
* @param s A pointer to the global solve state.
* @param transport The transport name for the IloCplex constructor.
* @param argc The argument count for the IloCplex constructor.
* @param argv The array of transport arguments for the IloCplex
* constructor.
* @param modelfile Name of the model to be loaded into the worker.
* @param output The output mode.
* @param objdiff The minimal difference between so that two
* consecutive objective function values are considered
* different.
*/
Worker(IloEnv env, int i, SolveState *s, char const *transport,
int argc, char const **argv, char const *modelfile,
OUTPUT output, double objdiff)
: idx(i), state(s), model(env), cplex(0), handle(0),
primal(IloInfinity), dual(-IloInfinity),
obj(env), x(env), rng(env), infoHandler(this), outb(idx), outs(&outb)
{
try {
// Create remote object, setup output and load the model.
cplex = IloCplex(model, transport, argc, argv);
switch (output) {
case OUTPUT_SILENT:
// Disable output on the output and warning stream.
cplex.setOut(env.getNullStream());
cplex.setWarning(env.getNullStream());
break;
case OUTPUT_PREFIXED:
// Redirect output to our custom stream.
cplex.setOut(outs);
cplex.setWarning(outs);
break;
case OUTPUT_LOG:
// Nothing to do here. By default output is enabled.
break;
}
cplex.importModel(model, modelfile, obj, x, rng);
if ( obj.getSense() == IloObjective::Minimize ) {
primal = -IloInfinity;
dual = IloInfinity;
}
// We set the thread count for each solver to 1 so that we do not
// run into problems if multiple solves are performed on the same
// machine.
cplex.setParam(IloCplex::Param::Threads, 1);
// Each worker runs with a different random seed. This way we
// get different paths through the tree even if the other
// parameter settings are the same.
cplex.setParam(IloCplex::Param::RandomSeed, idx);
// Apply parameter settings.
for (class ParamValue const *vals = settings[idx % NUMSETTINGS].values;
vals->isValid(); ++vals)
vals->apply(cplex);
// Install callback and set objective change.
int status = cplex.userfunction (USERACTION_ADDCALLBACK,
0, NULL, 0, 0, NULL);
if ( status )
throw status;
IloCplex::Serializer s;
s.add(objdiff);
status = cplex.userfunction (USERACTION_CHANGEOBJDIFF,
s.getRawLength(), s.getRawData(),
0, 0, NULL);
if ( status )
throw status;
// Register the handler that will process info messages sent
// from the worker.
cplex.setRemoteInfoHandler(&infoHandler);
// Everything is setup. Launch the asynchronous solve.
handle = cplex.solve(true);
} catch (...) {
// In case of an exception we need to take some special
// cleanup actions. Note that if we get here then the
// solve cannot have been started and we don't need to
// kill or join the asynchronous solve.
if ( cplex.getImpl() )
cplex.end();
rng.end();
x.end();
obj.end();
model.end();
throw;
}
}