Cycle greedIt(const Matrix &mat)
{
size_t n = mat.size();
Cycle cycle;
vector<bool> visited(n, false);
visited[0] = true;
int i = 0;
while (cycle.size() != n)
{
int best_j = 0;
int best_val = INT32_MAX;
for (int j = 0; j < n; j++) {
if (visited[j] || best_val < mat[i][j]) continue;
best_j = j;
best_val = mat[i][j];
}
cycle.push_back(best_j);
visited[best_j] = true;
i = best_j;
}
cycle.push_front(0);
return cycle;
}
Cycle twoOptAllowNeg(const Matrix &mat, Cycle cycle, int default_neg, int diff_d, int min)
{
size_t cycle_size = cycle.size();
int improve = 0;
bool distance_treshold = false;
while (improve < 10)
{
int neg_imp = default_neg;
int best_distance = countCycle(mat, cycle);
for (int i = 1; i < cycle_size - 1; i++)
{
for (int j = i + 1; j < cycle_size - 1; j++)
{
Cycle new_cycle = swapCities(cycle, i, j);
int new_distance = countCycle(mat, new_cycle);
int diff_distance = new_distance - best_distance;
if (distance_treshold)
{
if ((new_distance < min) && (new_distance < best_distance))
{
improve = 0;
neg_imp--;
cycle = new_cycle;
best_distance = new_distance;
}
}
else
{
if (new_distance < best_distance || (diff_distance < diff_d && neg_imp > 0))
{
improve = 0;
neg_imp--;
cycle = new_cycle;
best_distance = new_distance;
if (new_distance < min) distance_treshold = true;
}
}
}
}
improve++;
}
return cycle;
}
Cycle swapCities(const Cycle &cycle, const int &a, const int &b)
{
Cycle n_cycle;
size_t cycle_size = cycle.size();
Cycle::const_iterator it;
vector<int> vcycle;
for (const auto &c : cycle)
vcycle.push_back(c);
for ( int c = 0; c <= a - 1; ++c )
n_cycle.push_back(vcycle[c]);
for (int c = a, dec = 0; c <= b; ++c, dec++)
n_cycle.push_back(vcycle[b - dec]);
for ( int c = b + 1; c < cycle_size; ++c )
n_cycle.push_back(vcycle[c]);
return n_cycle;
}
bool cycle_cmp_bool(const Cycle & a, const Cycle & b)
{
return a.size() < b.size();
}