void naryRandom::generateTernCtr( int i, int j, int k, long nogoods, Cost costMin, Cost costMax )
{
int a,b,c,dice;
EnumeratedVariable* x = (EnumeratedVariable*) wcsp.getVar(i);
EnumeratedVariable* y = (EnumeratedVariable*) wcsp.getVar(j);
EnumeratedVariable* z = (EnumeratedVariable*) wcsp.getVar(k);
int mx = x->getDomainInitSize();
int my = y->getDomainInitSize();
int mz = z->getDomainInitSize();
long total_nogoods = mx*my*mz;
vector<Cost> costs;
for (a = 0; a < mx; a++)
for (b = 0; b < my; b++)
for (c = 0; c < mz; c++)
costs.push_back(MIN_COST);
while(nogoods>0) {
dice = myrand() % total_nogoods;
for(a=0;a<mx;a++)
for(b=0;b<my;b++)
for(c=0;c<mz;c++) {
if(costs[my*mz*a + b*mz + c] == MIN_COST) {
if(dice == 0) {
costs[my*mz*a + b*mz + c] = ToulBar2::costMultiplier * randomCost(costMin, costMax);
nogoods--;
total_nogoods--;
a=mx;b=my;c=mz;
}
dice--;
}
}
}
wcsp.postTernaryConstraint(i,j,k,costs);
}
void naryRandom::generateNaryCtr( vector<int>& indexs, long nogoods, Cost costMin, Cost costMax)
{
int i;
int arity = indexs.size();
EnumeratedVariable** scopeVars = new EnumeratedVariable * [arity];
int* scopeIndexs = new int [arity];
Char* tuple = new Char [arity+1];
Cost Top = wcsp.getUb();
if(costMax < Top) Top = costMax;
for(i = 0; i<arity; i++) {
scopeIndexs[i] = indexs[i];
scopeVars[i] = (EnumeratedVariable*) wcsp.getVar(indexs[i]);
tuple[i] = 0 + CHAR_FIRST;
}
tuple[arity] = '\0';
Constraint* nctr = wcsp.getCtr( wcsp.postNaryConstraintBegin(scopeIndexs, arity, Top) );
String s(tuple);
while(nogoods>0) {
for(i = 0; i<arity; i++) s[i] = myrand() % scopeVars[i]->getDomainInitSize() + CHAR_FIRST;
Cost c = ToulBar2::costMultiplier * randomCost(MIN_COST, costMax);
nctr->setTuple(s, c, scopeVars);
nogoods--;
}
nctr->propagate();
delete [] scopeIndexs;
delete [] scopeVars;
delete [] tuple;
}
void naryRandom::generateSubModularBinCtr( int i, int j, Cost costMin, Cost costMax )
{
int a,b;
EnumeratedVariable* x = (EnumeratedVariable*) wcsp.getVar(i);
EnumeratedVariable* y = (EnumeratedVariable*) wcsp.getVar(j);
int mx = x->getDomainInitSize();
int my = y->getDomainInitSize();
vector<Cost> costs;
for (a = 0; a < mx; a++)
for (b = 0; b < my; b++)
costs.push_back(MIN_COST);
// row generation
for (a = 0; a < mx; a++) {
if(myrand() % 2) {
Cost c = ToulBar2::costMultiplier * randomCost(costMin, costMax);
for (b = 0; b < my; b++) costs[my*a+b] += c;
}
}
// col generation
for (b = 0; b < my; b++) {
if(myrand() % 2) {
Cost c = ToulBar2::costMultiplier * randomCost(costMin, costMax);
for (a = 0; a < mx; a++) costs[my*a+b] += c;
}
}
// rectangle generation
int nrect = myrand() % mx;
while(nrect) {
Cost c = ToulBar2::costMultiplier * randomCost(costMin, costMax);
int lx = myrand() % (mx-1);
int ly = myrand() % (my-1);
for (a = 0; a < lx; a++)
for (b = 0; b < ly; b++) {
costs[my*(mx-a-1) + b] += c;
}
nrect--;
}
wcsp.postBinaryConstraint(i,j,costs);
}
int main(int argc, char * argv[])
{
mysrand(getpid());
tb2init(); // must be call before setting specific ToulBar2 options and creating a model
ToulBar2::verbose = -1; // change to 0 to see more information
// uncomment if Virtual Arc Consistency (equivalent to Augmented DAG algorithm) enable
// ToulBar2::vac = 1; // option -A
// ToulBar2::vacValueHeuristic = true; // option -V
// uncomment if partial Limited Discrepancy Search enable
// ToulBar2::lds = 1; // option -l=1
// uncomment if INCOP local search enable
// ToulBar2::incop_cmd = Incop_cmd; // option -i
// create a problem with three 0/1 variables
WeightedCSPSolver *solver = WeightedCSPSolver::makeWeightedCSPSolver(STORE_SIZE, MAX_COST);
int x = solver->getWCSP()->makeEnumeratedVariable("x",0,1); // note that for efficiency issue, I assume domain values start at zero (otherwise remove flag -DWCSPFORMATONLY in Makefile)
int y = solver->getWCSP()->makeEnumeratedVariable("y",0,1);
int z = solver->getWCSP()->makeEnumeratedVariable("z",0,1);
// add random unary cost functions on each variable
{
vector<Cost> costs(2, 0);
costs[0] = randomCost(0,100);
costs[1] = randomCost(0,100);
solver->getWCSP()->postUnary(x, costs);
costs[0] = randomCost(0,100);
costs[1] = randomCost(0,100);
solver->getWCSP()->postUnary(y, costs);
costs[0] = randomCost(0,100);
costs[1] = randomCost(0,100);
solver->getWCSP()->postUnary(z, costs);
}
// add binary cost functions (Ising) on each pair of variables
{
vector<Cost> costs;
for (unsigned int i = 0 ; i < 2; i++) {
for (unsigned int j = 0 ; j < 2; j++) {
costs.push_back((solver->getWCSP()->toValue(x, i) == solver->getWCSP()->toValue(y, j)) ? 0 : 30); // penalizes by a cost=30 if variables are assigned to different values
}
}
solver->getWCSP()->postBinaryConstraint(x,y,costs);
solver->getWCSP()->postBinaryConstraint(x,z,costs);
solver->getWCSP()->postBinaryConstraint(y,z,costs);
}
// add a ternary hard constraint (x+y=z)
{
vector<Cost> costs;
for (unsigned int i = 0 ; i < 2; i++) {
for (unsigned int j = 0 ; j < 2; j++) {
for (unsigned int k = 0 ; k < 2; k++) {
costs.push_back((solver->getWCSP()->toValue(x, i) + solver->getWCSP()->toValue(y, j) == solver->getWCSP()->toValue(z, k)) ? 0 : MAX_COST);
}
}
}
solver->getWCSP()->postTernaryConstraint(x,y,z,costs);
}
solver->getWCSP()->sortConstraints(); // to be done before search
solver->getWCSP()->histogram(); // to be done before search
// int verbose = ToulBar2::verbose;
// ToulBar2::verbose = 5; // high verbosity to see the cost functions
// solver->getWCSP()->print(cout);
// ToulBar2::verbose = verbose;
if (solver->solve()) {
// show optimal solution
vector<Value> sol;
Cost optimum = solver->getSolution(sol);
cout << "Optimum=" << optimum << endl;
cout << "Solution: x=" << sol[x] << " ,y=" << sol[y] << " ,z=" << sol[z] << endl;
} else {
cout << "No solution found!" << endl;
}
cout << "Initial problem lower bound: " << solver->getWCSP()->getLb() << endl;
cout << "end." << endl;
return 0;
}
void naryRandom::Input( int in_n, int in_m, vector<int>& p, bool forceSubModular )
{
n = in_n;
m = in_m;
assert(p.size() >= 2);
int i,arity;
vector<int> indexs;
vector<long> totalCtrs;
vector<long> numCtrs;
int maxa = p.size();
for(arity=0; arity <= maxa; arity++) {
if(arity < 2) numCtrs.push_back(0);
else numCtrs.push_back(p[arity-1]);
}
if (forceSubModular) {
numCtrs[maxa] = (numCtrs[maxa-1] * numCtrs[maxa]) / 100;
maxa--;
}
for(i=0;i<n;i++) {
string varname = to_string(i);
wcsp.makeEnumeratedVariable(varname,0,m-1);
}
for(arity=maxa;arity>1;arity--) {
long nogoods = (long) (((double)p[0] / 100.) * pow((double)m, arity));
//long totalarraysize = (long) pow( (double)n, arity);
long tCtrs = 1;
set<long> scopes;
for(i=0; i < arity; i++) tCtrs *= (n - i);
for(i=2; i <= arity; i++) tCtrs /= i;
if(numCtrs[arity] > tCtrs) {
cout << numCtrs[arity] << " " << arity << "ary constraints and the maximum is " << tCtrs << endl;
numCtrs[arity] = tCtrs;
}
while(numCtrs[arity]) {
bool oneadded = false;
int dice = myrand() % tCtrs;
ini(indexs,arity);
do {
if(scopes.end() == scopes.find(toIndex(indexs))) {
if(dice == 0) {
scopes.insert( toIndex(indexs) );
if(arity > 1) {
switch(arity) {
case 2:
if(!forceSubModular || numCtrs[arity] > numCtrs[maxa+1]) generateBinCtr(indexs[0],indexs[1],nogoods);
else generateSubModularBinCtr(indexs[0],indexs[1],SMALL_COST,MEDIUM_COST);
break;
case 3:
generateTernCtr(indexs[0],indexs[1],indexs[2],nogoods);
break;
default: generateNaryCtr(indexs,nogoods);
}
}
tCtrs--;
numCtrs[arity]--;
oneadded = true;
}
dice--;
}
} while(inc(indexs) && !oneadded);
}
}
for(i=0;i<n;i++) {
EnumeratedVariable* x = (EnumeratedVariable*) wcsp.getVar(i);
for (unsigned int a = 0; a < x->getDomainInitSize(); a++)
{
x->project(x->toValue(a), ToulBar2::costMultiplier * randomCost(MIN_COST, MEDIUM_COST));
}
x->findSupport();
}
if(forceSubModular) {
for(i=0;i<n;i++) {
EnumeratedVariable* x = (EnumeratedVariable*) wcsp.getVar(i);
x->permuteDomain(10);
}
}
}
