private void createMember(List <HerdMember> fromList, List <HerdMember> outList)
{
int number = random.Next(fromList.Count);
HerdMember member = new HerdMember(vertices, distanceTable, capacityTable, fromList[number].solution.capacityPath, target);
System.Threading.Monitor.Enter(semaphore);
outList.Add(member);
System.Threading.Monitor.Exit(semaphore);
}
public void firstGeneration()
{
for (int i = 1; i < mi; i++)
{
HerdMember member = members[0];
createMember(member, members);
}
bestMember = chooseBest(members);
}
private void oneIteration()
{
List <HerdMember> newPopulation = generateNewPopulationMultiThreads();
members = mergePopulations(members, newPopulation);
HerdMember bestChild = chooseBest(newPopulation);
if (bestChild.solution.finalValue > bestMember.solution.finalValue)
{
bestMember = bestChild;
}
doSelection(2);
}
private HerdMember chooseBest(List <HerdMember> list)
{
HerdMember toReturn = list.First();
foreach (var v in list)
{
if (v.solution.finalValue > toReturn.solution.finalValue)
{
toReturn = v;
}
}
return(toReturn);
}
private void rouletteSelection()
{
double sum = 0;
foreach (var v in members)
{
sum += v.solution.finalValue;
}
List <HerdMember> newMembers = new List <HerdMember>();
for (int i = 0; i < mi; i++)
{
HerdMember toAdd = rouletteOnePoint(sum);
newMembers.Add(toAdd);
}
members = newMembers;
}
static void Main(string[] args)
{
string edgePath = "C://Users//user//Desktop//dane//przykladowe_dane//gen_50_d_2.xml";
string parametersPath = "C://Users//user//Desktop//dane//przykladowe_dane//gen_50_d_2_0_4_1.txt";
Graph graph = new Graph();
Globals.stopWatch.Start();
graph.readEdges(edgePath);
Globals.stopWatch.Stop();
Globals.printElapsedTimeResetWatch(Globals.stopWatch.Elapsed, "Loaded edges");
Globals.stopWatch.Start();
graph.readParameters(parametersPath);
Globals.stopWatch.Stop();
Globals.printElapsedTimeResetWatch(Globals.stopWatch.Elapsed, "Loaded parameters");
Globals.stopWatch.Start();
double[,] distanceTable = graph.createDistanceTable();
double[,] capacityTable = graph.createCapacityTable();
Globals.stopWatch.Stop();
Globals.printElapsedTimeResetWatch(Globals.stopWatch.Elapsed, "Created distance and capacity tables");
Globals.stopWatch.Start();
HerdMember member = new HerdMember(graph.vertices, distanceTable, capacityTable, graph.sourceNumber, graph.targetNumber);
Globals.stopWatch.Stop();
Globals.printElapsedTimeResetWatch(Globals.stopWatch.Elapsed, "Found first solution");
member.solution.printSolution();
Globals.stopWatch.Start();
Population population = new Population(graph, 10, 15, 1000, 1000000000, 10, "roulette");
population.runAlgorithm();
Globals.stopWatch.Stop();
Globals.printElapsedTimeResetWatch(Globals.stopWatch.Elapsed, "Finished algorithm");
population.bestMember.solution.printSolution();
Console.ReadKey();
}
public Population(Graph graph, int m, int l, int iter, double val, double time, string sel)
{
mi = m;
lambda = l;
iterations = iter;
minValue = val;
maxTime = time;
distanceTable = graph.createDistanceTable();
capacityTable = graph.createCapacityTable();
source = graph.sourceNumber;
target = graph.targetNumber;
vertices = graph.vertices;
selection = sel;
HerdMember member = new HerdMember(graph.vertices, distanceTable, capacityTable, source, target);
bestMember = member;
members = new List <HerdMember>();
members.Add(member);
}
private void createMember(HerdMember member, List <HerdMember> outList)
{
HerdMember toAdd = new HerdMember(vertices, distanceTable, capacityTable, member.solution.capacityPath, target);
outList.Add(toAdd);
}
