//**********************************************BBAlgorithm*********************************************************************************
/// <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];
// TODO: Add your implementation for a branch and bound solver here.
//Initalize variables. Takes O(1) space and time
int numOfCitiesLeft = Cities.Length;
int numOfSolutions = 0;
int numOfStatesCreated = 0;
int numOfStatesNotExpanded = 0;
//Initalize time variable for stopping the algorithm after the default of 60 seconds. Takes O(1) space and time
DateTime start = DateTime.Now;
DateTime end = start.AddSeconds(time_limit / 1000);
//Create initial root state and set its priority to its lower bound. Takes O(n^2) space and time as discussed above
TSPState initialState = createInitialState();
numOfStatesCreated++;
initialState.setPriority(calculateKey(numOfCitiesLeft - 1, initialState.getLowerBound()));
//Create initial BSSF greedily
double bssfBound = createGreedyBssf();
PriorityQueue queue = new PriorityQueue(Cities.Length);
queue.insert(initialState);
// Branch and Bound until the queue is empty, we have exceeded the time limit, or we found the optimal solution
/* This loop will have a iterate 2^n times approximately with expanding and pruning for each state, then for each state it
* does O(n^2) work by reducing the matrix, so over all O((n^2)*(2^n)) time and space as well as it creates a nxn
* matrix for each state*/
while (!queue.isEmpty() && DateTime.Now < end && queue.getMinLB() != bssfBound)
{
// Grab the next state in the queue
TSPState currState = queue.deleteMin();
// check if lower bound is less than the BSSF, else prune it
if (currState.getLowerBound() < bssfBound)
{
// Branch and create the child states
for (int i = 0; i < Cities.Length; i++)
{
// First check that we haven't exceeded the time limit
if (DateTime.Now >= end)
{
break;
}
// Make sure we are only checking cities that we haven't checked already
if (currState.getPath().Contains(Cities[i]))
{
continue;
}
// Create the State
double[,] oldCostMatrix = currState.getCostMatrix();
double[,] newCostMatrix = new double[Cities.Length, Cities.Length];
// Copy the old array in the new one to modify the new without affecting the old
for (int k = 0; k < Cities.Length; k++)
{
for (int l = 0; l < Cities.Length; l++)
{
newCostMatrix[k, l] = oldCostMatrix[k, l];
}
}
City lastCityinCurrState = (City)currState.getPath()[currState.getPath().Count - 1];
double oldLB = currState.getLowerBound();
setUpMatrix(ref newCostMatrix, Array.IndexOf(Cities, lastCityinCurrState), i, ref oldLB);
double newLB = oldLB + reduceMatrix(ref newCostMatrix);
ArrayList oldPath = currState.getPath();
ArrayList newPath = new ArrayList();
foreach (City c in oldPath)
{
newPath.Add(c);
}
newPath.Add(Cities[i]);
TSPState childState = new TSPState(ref newPath, ref newLB, ref newCostMatrix);
numOfStatesCreated++;
// Prune States larger than the BSSF
if (childState.getLowerBound() < bssfBound)
{
City firstCity = (City)childState.getPath()[0];
City lastCity = (City)childState.getPath()[childState.getPath().Count - 1];
double costToLoopBack = lastCity.costToGetTo(firstCity);
// If we found a solution and it goes back from last city to first city
if (childState.getPath().Count == Cities.Length && costToLoopBack != double.MaxValue)
{
childState.setLowerBound(childState.getLowerBound() + costToLoopBack);
bssf = new TSPSolution(childState.getPath());
bssfBound = bssf.costOfRoute();
numOfSolutions++;
numOfStatesNotExpanded++; // this state is not expanded because it is not put on the queue
}
else
{
// Set the priority for the state and add the new state to the queue
numOfCitiesLeft = Cities.Length - childState.getPath().Count;
childState.setPriority(calculateKey(numOfCitiesLeft, childState.getLowerBound()));
queue.insert(childState);
}
}
else
{
numOfStatesNotExpanded++; // States that are pruned are not expanded
}
}
}
currState = null;
}
numOfStatesNotExpanded += queue.getSize(); // if the code terminated before queue is empty, then those states never got expanded
Console.WriteLine("Number of states generated: " + numOfStatesCreated);
Console.WriteLine("Number of states not Expanded: " + numOfStatesNotExpanded);
Console.WriteLine("Max Number of states put in queue: " + queue.getMaxNumOfItems());
end = DateTime.Now;
TimeSpan diff = end - start;
double seconds = diff.TotalSeconds;
results[COST] = System.Convert.ToString(bssf.costOfRoute()); // load results into array here, replacing these dummy values
results[TIME] = System.Convert.ToString(seconds);
results[COUNT] = System.Convert.ToString(numOfSolutions);
return(results);
}
/// <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];
int solutionCount = 0;
Stopwatch timer = new Stopwatch();
PriorityQueue <State> pQueue = new PriorityQueue <State>();
int maxStoredStates = 0;
int bssfUpdates = 0;
int totalStatesCreated = 0;
int totalStatesPruned = 0;
timer.Start();
string[] intialResults = defaultSolveProblem();
double bestCostSoFar = Int32.Parse(intialResults[COST]);
Console.WriteLine("BestCostSoFar: " + bestCostSoFar);
State initialState = initializeState();
this.reduceState(ref initialState);
pQueue.insert(initialState, (int)initialState.lowerBound);
while (!pQueue.isEmpty() && timer.Elapsed.Seconds < 60) // while queue is not empty or has not passed 60 seconds
{
State parentState = pQueue.deleteMin();
if (parentState.lowerBound >= bestCostSoFar) // trim queue if state has worse bound than bssf
{
totalStatesPruned++;
continue;
}
for (int i = 0; i < this.Cities.Length; i++)
{
if (!parentState.visited.Contains(i))
{
// createChild
totalStatesCreated++;
State childState = parentState.getCopy();
this.addCityToRoute(ref childState, i);
this.reduceState(ref childState);
if (childState.route.Count == this.Cities.Count()) // if route is complete
{
TSPSolution newSolution = new TSPSolution(childState.route);
double cost = newSolution.costOfRoute();
if (cost < bestCostSoFar)
{
bssfUpdates++;
bestCostSoFar = cost;
bssf.Route = childState.route;
}
}
else // route is not complete
{
if (childState.lowerBound < bestCostSoFar) // don't insert in queue if state has worse bound than bssf
{
pQueue.insert(childState, (int)childState.lowerBound);
if (pQueue.getCount() > maxStoredStates)
{
maxStoredStates = pQueue.getCount();
}
}
else
{
totalStatesPruned++;
}
}
}
}
}
timer.Stop();
results[COST] = costOfBssf().ToString();
results[TIME] = timer.Elapsed.ToString();
results[COUNT] = solutionCount.ToString();
Console.WriteLine("===================================");
Console.WriteLine("StatesCreated: " + totalStatesCreated);
Console.WriteLine("StatesPruned: " + totalStatesPruned);
Console.WriteLine("bssfUpdates: " + bssfUpdates);
Console.WriteLine("MaxStoredStates: " + maxStoredStates);
return(results);
}