CGeneticTSPSolver::CGeneticTSPSolver(CCityLocData *inputData, int nGenes, int nGroups) {
cityLocData = inputData;
nPopulation = nGenes;
nNumberOfGroups = nGroups;
nCities = cityLocData->numCities;
mFitness = new float[nPopulation];
mPhenotype = new int*[nPopulation];
initSolver();
}
TEST(LPInitSolver, initialization) {
LP lp = simpleLP1();
LPInitSolver initSolver(lp);
GaussianFactorGraph::shared_ptr initOfInitGraph =
initSolver.buildInitOfInitGraph();
VectorValues x0 = initOfInitGraph->optimize();
VectorValues expected_x0;
expected_x0.insert(1, Vector::Zero(2));
CHECK(assert_equal(expected_x0, x0, 1e-10));
double y0 = initSolver.compute_y0(x0);
double expected_y0 = 0.0;
DOUBLES_EQUAL(expected_y0, y0, 1e-7);
Key yKey = 2;
LP::shared_ptr initLP = initSolver.buildInitialLP(yKey);
LP expectedInitLP;
expectedInitLP.cost = LinearCost(yKey, kOne);
expectedInitLP.inequalities.push_back(LinearInequality(
1, Vector2(-1, 0), 2, Vector::Constant(1, -1), 0, 1)); // -x1 - y <= 0
expectedInitLP.inequalities.push_back(LinearInequality(
1, Vector2(0, -1), 2, Vector::Constant(1, -1), 0, 2)); // -x2 - y <= 0
expectedInitLP.inequalities.push_back(
LinearInequality(1, Vector2(1, 2), 2, Vector::Constant(1, -1), 4,
3)); // x1 + 2*x2 - y <= 4
expectedInitLP.inequalities.push_back(
LinearInequality(1, Vector2(4, 2), 2, Vector::Constant(1, -1), 12,
4)); // 4x1 + 2x2 - y <= 12
expectedInitLP.inequalities.push_back(
LinearInequality(1, Vector2(-1, 1), 2, Vector::Constant(1, -1), 1,
5)); // -x1 + x2 - y <= 1
CHECK(assert_equal(expectedInitLP, *initLP, 1e-10));
LPSolver lpSolveInit(*initLP);
VectorValues xy0(x0);
xy0.insert(yKey, Vector::Constant(1, y0));
VectorValues xyInit = lpSolveInit.optimize(xy0).first;
VectorValues expected_init;
expected_init.insert(1, Vector::Ones(2));
expected_init.insert(2, Vector::Constant(1, -1));
CHECK(assert_equal(expected_init, xyInit, 1e-10));
VectorValues x = initSolver.solve();
CHECK(lp.isFeasible(x));
}
PBDSolver::PBDSolver()
{
initSolver();
}
