/// <summary>
/// Creates a subtree in the form of a single line from a list of nodes
/// </summary>
/// <param name="nodes">The nodes to be in the subtree</param>
/// <returns>The root of a subtree with the nodes in a single line</returns>
private RecursiveTree <Node> CreateLine(List <Node> nodes)
{
RecursiveTree <Node> root = new RecursiveTree <Node>(nodes[0]);
RecursiveTree <Node> parent = root;
for (int i = 1; i < nodes.Count; i++)
{
RecursiveTree <Node> node = new RecursiveTree <Node>(nodes[i])
{
Parent = parent
};
parent.AddChild(node);
parent = node;
}
return(root);
}
public Neighbour <RecursiveTree <Node> > GetRandomNeighbour(RecursiveTree <Node> data)
{
List <Neighbour <RecursiveTree <Node> > > neighbourlist = new List <Neighbour <RecursiveTree <Node> > >();
// Create a random MoveUpNeighbour
Neighbour <RecursiveTree <Node> > move = MoveUpNeighbourSpace.GetRandomNeighbour(data);
neighbourlist.Add(move);
// Generate Splits amount of random SplitNeighbours
for (int i = 0; i < Splits; i++)
{
Neighbour <RecursiveTree <Node> > split = SplitNeighbourSpace.GetRandomNeighbour(data);
neighbourlist.Add(split);
}
// Return the list with the single Move and multiple SplitNeighbours
return(new MultipleNeighbourNeighbour <RecursiveTree <Node> >(neighbourlist));
}
/// <summary>
/// Recursive method used for computing the heuristic tree, computes the tree for a subset of nodes
/// </summary>
/// <param name="nodes">All nodes in the entire tree</param>
/// <param name="ancestors">The list of ancestors for the current subtree</param>
/// <param name="left">The INCLUSIVE index in nodes where the current subtree starts</param>
/// <param name="right">The EXCLUSIVE index in nodes where the current subtree ends</param>
/// <param name="timer">A RUNNING! timer to keep track of how long this computation is allowed to take</param>
/// <param name="maxTimeAllowed">The maximum time this computation is allowed to take</param>
/// <param name="fast">Whether heuristics should be updated during the computation. Fast means they are not updated</param>
/// <returns>The resulting heuristic tree for this subset of nodes</returns>
private RecursiveTree <Node> RecGetHeuristicTree(Node[] nodes, HashSet <Node> ancestors, int left, int right, Stopwatch timer, double maxTimeAllowed, bool fast) // Left inclusive, right exclusive
{
// Compute the array for this subset of nodes
subArray = nodes.Skip(left).Take(right - left);
// If the time is up, return the nodes in a single line with for this subtree
if (timer.Elapsed.TotalSeconds >= maxTimeAllowed)
{
return(CreateLine(subArray.ToList()));
}
// If the new tree has only one node, return this node
if (left - right == 1)
{
return(new RecursiveTree <Node>(nodes[left]));
}
// Select a node as the root of this subtree based on the heuristics of the nodes in this subgraph and compute the connected component when this node is removed
// These components are the subtrees that are children of the selected node
Node selectedNode = GetHeuristicNode(subArray, fast);
RecursiveTree <Node> newTree = new RecursiveTree <Node>(selectedNode);
ComputeConnectedComponents(nodes, ancestors, selectedNode, left, right);
Tuple <int, int>[] borders = ComputeNewSubgraphBorders(nodes, left);
// For each of the new subtrees, do a recursive call to this method to compute it
for (int i = 0; i < borders.Length; i++)
{
RecursiveTree <Node> ChildTree = RecGetHeuristicTree(nodes, ancestors, borders[i].Item1, borders[i].Item2, timer, maxTimeAllowed, fast);
ChildTree.Parent = newTree;
newTree.AddChild(ChildTree);
}
// Remove the selected node from the ancestors so the possible other subtrees of the parent of this subtree do not accidentaly use it.
// We do this to avoid having to copy the entire ancestors list for each recursive call
ancestors.Remove(selectedNode);
return(newTree);
}
/// <summary>
/// Create a RecursiveTree with all nodes in a single line (each tree has exactly one child, except for the single leaf)
/// </summary>
/// <returns>The root of a RecursiveTree in a line</returns>
public static RecursiveTree <Node> LineRecursiveTree(ref List <RecursiveTree <Node> > allRecTreeNodes, Node[] allNodes)
{
allRecTreeNodes = new List <RecursiveTree <Node> >();
int numberOfNodes = allNodes.Length;
// Create the root of the line
RecursiveTree <Node> recTree = new RecursiveTree <Node>(allNodes[0]);
allRecTreeNodes.Add(recTree);
// Loop through all other nodes and create trees for them with the correct parent and cildren references
RecursiveTree <Node> child = recTree;
for (int i = 1; i < numberOfNodes; i++)
{
Node newNode = allNodes[i];
RecursiveTree <Node> parent = new RecursiveTree <Node>(newNode);
child.Parent = parent;
parent.AddChild(child);
child = parent;
allRecTreeNodes.Add(parent);
}
return(recTree);
}
/// <summary>
/// Operation that removes a certain child from a node
/// </summary>
/// <param name="node">The node from which the child is removed</param>
/// <param name="child">The child that is removed</param>
public RemoveChildOperation(RecursiveTree <Node> node, RecursiveTree <Node> child)
{
this.node = node;
this.child = child;
node.RemoveChild(child);
}
/// <summary>
/// Changes the parent of a node
/// </summary>
/// <param name="node">The node that needs a new parent</param>
/// <param name="newParent">The new parent of the node</param>
public ChangeParentOperation(RecursiveTree <Node> node, RecursiveTree <Node> newParent)
{
this.node = node;
oldParent = node.Parent;
node.Parent = newParent;
}
/// <summary>
/// Operation that adds multiple children to a node
/// </summary>
/// <param name="node">The node to add the children to</param>
/// <param name="children">The collection of children to be added</param>
public AddChildrenOperation(RecursiveTree <Node> node, IEnumerable <RecursiveTree <Node> > children)
{
this.node = node;
this.children = children;
node.AddChildren(children);
}
/// <summary>
/// Operation that removes all children from a node
/// </summary>
/// <param name="node">The node from which the children are removed</param>
public RemoveAllChildrenOperation(RecursiveTree <Node> node)
{
this.node = node;
children = node.Children;
node.RemoveAllChildren();
}
/// <summary>
/// Operation that removes a list of children from a node
/// </summary>
/// <param name="node">The node from which the children are removed</param>
/// <param name="children">The children that are removed from the node</param>
public RemoveChildrenOperation(RecursiveTree <Node> node, IEnumerable <RecursiveTree <Node> > children)
{
this.node = node;
this.children = node.Children;
node.RemoveChildren(children);
}
/// <summary>
/// Execute the program using simulated annealing
/// </summary>
/// <param name="fileName">The name of the file to be run, or empty if the console is used</param>
/// <param name="console">Whether input form the console is used. If so, the program runs in quiet mode</param>
private static void SimulatedAnnealing(string fileName = "", bool console = true)
{
if (!console)
{
Console.WriteLine($"Starting file {fileName}...");
}
// The stopwatch keeps track of the total running time of the program
stopwatchSingleRun.Start();
// Read the input, depending on whether the console is used a file is being read or console input
Node[] inputAsNodes;
if (!console)
{
inputAsNodes = IO.ReadInputAsNodes($"..\\..\\..\\..\\..\\Testcases\\{fileName}.gr", CENTER_RESEMBLANCE_CAP, ARTICULATION_POINT_MINIMUM);
}
else
{
inputAsNodes = IO.ReadInputAsNodes(CENTER_RESEMBLANCE_CAP, ARTICULATION_POINT_MINIMUM);
}
allNodes = inputAsNodes;
// Create instances for the simunlated annealing and recursivesplit classes
SimulatedAnnealing <State <RecursiveTree <Node> >, RecursiveTree <Node> > simulatedAnnealing =
new SimulatedAnnealing <State <RecursiveTree <Node> >, RecursiveTree <Node> >(random, START_TEMP, RESET_TEMPERATURE_THRESHOLD, TEMP_MULTIPLIER, MULTIPLY_TEMP_PER_ITERATIONS, stopwatchSingleRun, MAX_TIME_TOTAL_SECONDS);
RecursiveSplit recursiveSplit = new RecursiveSplit(inputAsNodes);
// Find an initial solution where all nodes are in a single line
RecursiveTreeState heurInitState = new RecursiveTreeState(BaseSolutionGenerator.LineRecursiveTree(ref allRecTreeNodes, allNodes), random, allRecTreeNodes);
bestStateSoFar = heurInitState.Data.ToString();
if (!console)
{
Console.WriteLine($"Line found with depth {heurInitState.Data.Root.Depth}.");
}
initialSolutionsTimer.Start();
RecursiveTree <Node> bestTree = null;
// Find an initial solution using the RecursiveSplit using a fast but bad heuristic
if (allNodes.Length <= FASTER_HEURISTIC_CAP)
{
double maxTime = MAX_TIME_INITIAL_SOLUTIONS_SECONDS;
if (allNodes.Length > INDEPENDENT_SET_CAP)
{
if (allNodes.Length > FAST_HEURISTIC_CAP)
{
maxTime *= 3;
}
else
{
maxTime *= 1.5;
}
}
else if (allNodes.Length > FAST_HEURISTIC_CAP)
{
maxTime *= 1.5;
}
bestTree = recursiveSplit.GetHeuristicTree(initialSolutionsTimer, maxTime, true);
if (!console)
{
Console.WriteLine($"Fastest heuristic tree found with depth {bestTree.Depth}.");
}
}
// Find an initial solution using the RecursiveSplit using a decent but pretty slow heuristic
if (allNodes.Length <= FAST_HEURISTIC_CAP)
{
double maxTime = MAX_TIME_INITIAL_SOLUTIONS_SECONDS;
if (allNodes.Length > INDEPENDENT_SET_CAP)
{
maxTime *= 3;
}
else if (allNodes.Length > FASTER_HEURISTIC_CAP)
{
maxTime *= 1.5;
}
else
{
maxTime *= 2;
}
RecursiveTree <Node> treeFromFastHeuristic = recursiveSplit.GetHeuristicTree(initialSolutionsTimer, maxTime, false);
if (bestTree == null || treeFromFastHeuristic.Depth < bestTree.Depth)
{
bestTree = treeFromFastHeuristic;
}
if (!console)
{
Console.WriteLine($"Fast heuristic tree found with depth {treeFromFastHeuristic.Depth}.");
}
}
// If the problem instance is small enough, we would like to try to find an initial solution using independent sets
if (allNodes.Length <= INDEPENDENT_SET_CAP)
{
double maxTime = MAX_TIME_INITIAL_SOLUTIONS_SECONDS * 3;
RecursiveTree <Node> treeFromIndependentSet = IndependentSet.TreeFromIndependentSets(allNodes, initialSolutionsTimer, maxTime);
if (bestTree == null || treeFromIndependentSet.Depth < bestTree.Depth)
{
bestTree = treeFromIndependentSet;
}
if (!console)
{
Console.WriteLine($"Independent set tree found with depth {treeFromIndependentSet.Depth}.");
}
}
// Recreate the tree and save the best found initial solution as the initial solution for simulated annealing
initialSolutionsTimer.Reset();
if (bestTree != null)
{
bestStateSoFar = bestTree.ToString();
RecreateTree(bestStateSoFar);
heurInitState = new RecursiveTreeState(allRecTreeNodes[0].Root, random, allRecTreeNodes);
}
if (allNodes.Length <= SIMULATED_ANNEALING_CAP)
{
simulatedAnnealing.Search(heurInitState, ref bestStateSoFar);
}
// If the input from the console is not used, write the output to a file, otherwise write it back to the console
if (!console)
{
using (StreamWriter sw = new StreamWriter($"..\\..\\..\\..\\..\\Results\\{fileName}.tree", false))
{
sw.Write(bestStateSoFar);
}
}
else
{
Console.Write(bestStateSoFar);
}
// Print the result and total time thus far
if (!console)
{
// Stop the total of this problem instace
stopwatchSingleRun.Stop();
Console.WriteLine($"Tree found with depth {bestStateSoFar.Split('\n')[0]} in {stopwatchSingleRun.Elapsed} seconds. (Total time: {allRunsTotalStopwatch.Elapsed})");
Console.WriteLine();
}
// Reset the stopwatch for the next time the program is run
stopwatchSingleRun.Reset();
}
public List <Neighbour <RecursiveTree <Node> > > GetAllNeighbours(RecursiveTree <Node> data)
{
throw new NotImplementedException(); // TODO: implement
}
/// <summary>
/// Remove a child from this RecursiveTree
/// </summary>
/// <param name="child">The child to be removed</param>
public void RemoveChild(RecursiveTree <V> child)
{
try { ChildrenList.Remove(child); }
catch { throw new Exception("Child is no child of this node!"); }
}
/// <summary>
/// Add a child to the children of this tree
/// </summary>
/// <param name="child">The child to be added</param>
public void AddChild(RecursiveTree <V> child)
{
ChildrenList.Add(child);
}
/// <summary>
/// Constructor for the RecursiveTree
/// </summary>
/// <param name="original">The original RecursiveTree this tree is supposed to be made off</param>
public RecursiveTree(RecursiveTree <V> original)
{
Value = original.Value;
ChildrenList = original.ChildrenList;
}
/// <summary>
/// Splits a subtree into multiple subtrees
/// </summary>
/// <param name="splitNode">The root of the subtree that is going to be split</param>
public SplitNeighbour(RecursiveTree <Node> splitNode)
{
this.splitNode = splitNode;
componentIndices = new Dictionary <Node, int>();
}
/// <summary>
/// Recursive method for calculating the best heuristic tree
/// </summary>
/// <param name="bestFoundSolution">The optimal solution thus far from this level of the tree, used for early stopping</param>
/// <param name="nodes">A list of all nodes in this subtree</param>
/// <param name="ancestors">The list of all ancestors of the current subtree</param>
/// <param name="checkedSubsets">A dictionary with checked subsets, used for memoization</param>
/// <returns>The optimal exact tree for the list of input nodes</returns>
private RecursiveTree <Node> RecGetBestTree(int bestFoundSolution, List <Node> nodes, HashSet <Node> ancestors, Dictionary <string, RecursiveTree <Node> > checkedSubsets)
{
// If the currently best found solution is smaller than the list of ancestors here, we cannot possibly improve it. Thus, we return an empty tree
if (bestFoundSolution < ancestors.Count + 1)
{
return(null);
}
// Check if we have already computed a subtree for this set of nodes, if so, return that tree
string asBits = NodeSubsetRepresentation(nodes);
if (checkedSubsets.ContainsKey(asBits) && checkedSubsets[asBits] != null)
{
RecursiveTree <Node> computedTree = new RecursiveTree <Node>(checkedSubsets[asBits]);
return(computedTree);
}
// Sort the nodes on their remaining degree value (descending) and recursively compute the best trees
HashSet <Node> nodesAsHash = new HashSet <Node>(nodes);
nodes = nodes.OrderByDescending(n => n.RemainingDegree(nodesAsHash)).ToList();
RecursiveTree <Node> bestTree = null;
foreach (Node selectedNode in nodes)
{
RecursiveTree <Node> newTree = new RecursiveTree <Node>(selectedNode);
HashSet <Node> beenList = new HashSet <Node>(ancestors)
{
selectedNode
};
bool broken = false;
foreach (Node n in nodes)
{
// Find the connected component this node is in
if (beenList.Contains(n))
{
continue;
}
List <Node> connectedNodes = DFS.All(n, (nn) => { return(true); }, beenList);
HashSet <Node> newHash = new HashSet <Node>(ancestors)
{
selectedNode
};
// Compute the best possible subtree for this connected component
RecursiveTree <Node> ChildTree = RecGetBestTree(bestFoundSolution, connectedNodes, newHash, checkedSubsets);
if (ChildTree == null)
{
// If the resulting tree is null, it is not a viable solution
broken = true;
break;
}
ChildTree.Parent = newTree;
newTree.AddChild(ChildTree);
}
// If we found a viable solution, update the best found solution thus far
if (!broken)
{
int newDepth = newTree.Depth;
if (newDepth + ancestors.Count < bestFoundSolution)
{
bestFoundSolution = newDepth + ancestors.Count;
bestTree = newTree;
}
}
}
// Save the tree in the memoization dictionary and return it
checkedSubsets[asBits] = bestTree;
return(bestTree);
}
