/// <summary>
/// performs a Branch and Bound search of the state space of partial tours
/// stops when time limit expires and uses BSSF as solution
/// </summary>
/// <returns>results array for GUI that contains three ints: cost of solution, time spent to find solution, number of solutions found during search (not counting initial BSSF estimate)</returns>
public string[] bBSolveProblem()
{
string[] results = new string[3];
////// My code //////
// Initialize variables
int countHittingBottom = 0;
int bssfUpdates = 0;
int maxUsedSize = 0;
int generatedNotes = 0;
int pruned = 0;
// First get the default
defaultSolveProblem();
double bssfCost = bssf.costOfRoute();
// Then do branch and bound
BnB a = new BnB();
priorityQueue h = new array();
string timeOut = "";
a.solve(h, 0, Cities, ref bssfCost, ref countHittingBottom, ref bssf, time_limit, ref timeOut, ref bssfUpdates, ref maxUsedSize, ref pruned, ref generatedNotes);
// Update text
results[COST] = bssfCost.ToString(); // load results into array here, replacing these dummy values
results[TIME] = timeOut;
results[COUNT] = bssfUpdates.ToString();
// MessageBox.Show("Max states "+maxUsedSize+ ". #BSSF updates: "+bssfUpdates+". States created: "+generatedNotes+". States pruned: "+pruned);
return(results);
}
void init(City[] Cities)
{
r = new Random(SEED);
species = new List <individual>(POPULATION);
// Initialize to random cities
for (int j = 0; j < POPULATION; j++)
{
species.Add(new individual(Cities.Length));
// Default solve problem
int[] perm = new int[Cities.Length];
//{
int i, swap, temp1, count = 0;
string[] results = new string[3];
ArrayList Route = new ArrayList();
Random rnd = new Random(j);
do
{
for (i = 0; i < perm.Length; i++) // create a random permutation template
{
perm[i] = i;
}
for (i = 0; i < perm.Length; i++)
{
swap = i;
while (swap == i)
{
swap = rnd.Next(0, Cities.Length);
}
temp1 = perm[i];
perm[i] = perm[swap];
perm[swap] = temp1;
}
Route.Clear();
for (i = 0; i < Cities.Length; i++) // Now build the route using the random permutation
{
Route.Add(Cities[perm[i]]);
}
bssf = new ProblemAndSolver.TSPSolution(Route);
count++;
} while (pAS.costOfBssf() == double.PositiveInfinity); // until a valid route is found
//}
species[j].copy(perm);
//int[] temp1 = ;
//species.Add(new individual(temp1));
species[j].cost = determineFitness(ref Cities, species[j].path);
}
// Borrowing my generate cost function
BnB temp = new BnB();
temp.generateCosts(Cities, out cityBase);
}