public void AnnealingTest1()
{
file = root + "\\bays29.xml";
XDocument tspFile = XDocument.Load(file);
AdjacencyMatrix testMatrix = new AdjacencyMatrix(tspFile);
SimulatedAnnealing test = new SimulatedAnnealing(testMatrix);
test.SetTemperature(10, (float)0.997, 1, 5000);
for (int i = 0; i < 1000; i++)
{
float result = test.Calculate();
if (result > 3500) // best result world known is 2020
{
Assert.Fail();
}
}
}
private static void Main(string[] args)
{
Options options = null;
Parser.Default.ParseArguments <Options>(args)
.WithParsed(res => options = res)
.WithNotParsed(err => Environment.Exit(1));
var stopWatch = Stopwatch.StartNew();
if (!File.Exists(options.FileName))
{
Console.WriteLine($"File {options.FileName} doesn't exist.");
return;
}
Console.Write($"Start parsing file: {options.FileName} ");
City city;
try
{
using (var reader = new StreamReader(options.FileName))
{
city = (City) new XmlSerializer(typeof(City)).Deserialize(reader);
}
}
catch (Exception e)
{
Console.WriteLine(
$"Unable to parse osm file: {e.Message}. See about downloading here: https://github.com/bruce-willis/City-Roads/blob/develop/docs/download.md");
return;
}
Console.WriteLine($"Elapsed time: {stopWatch.Elapsed}");
TimeHelper.MeasureTime(() => SvgHelper.GenerateSvg(city, options), "generationg svg file");
if (options.GenerateNodesList)
{
TimeHelper.MeasureTime(() => CsvHelper.WriteNodesInfo(options.OutputDirectory), "creating csv with nodes' information");
}
if (options.GenerateAdjacencyList)
{
TimeHelper.MeasureTime(() => CsvHelper.WriteAdjacencyList(options.OutputDirectory), "creating csv with adjacency list");
}
if (options.GenerateAdjacencyMatrix)
{
TimeHelper.MeasureTime(() => CsvHelper.WriteAdjacencyMatrix(options.OutputDirectory), "creating csv with adjacency matrix");
}
DistanceHelper.AddNodes(city);
if (options.FindShortestPathes)
{
DistanceHelper.CompareAlgorithms(options.OutputDirectory);
}
if (options.SolveSalesmanProblem)
{
Directory.CreateDirectory(Path.Combine(options.OutputDirectory, "Salesman"));
TimeHelper.MeasureTime(() => CommonSalesman.Distances.GetType(),
"calculating distances and pathes between destinations");
TimeHelper.MeasureTime(() => NearestNeighbour.Calculate(options.OutputDirectory),
"solving travelling salesman problem using nearest neighbour");
TimeHelper.MeasureTime(() => NearestNeighbour.Calculate(options.OutputDirectory, withRandom: true),
"solving travelling salesman problem using nearest neighbour and random");
//int i = 0;
//double d1, d2;
//do
//{
// d1 = NearestNeighbour.Calculate(city, options.OutputDirectory);
// d2 = NearestNeighbour.CalculateWithRandom(city, options.OutputDirectory);
// Console.WriteLine(i++);
//} while (d1 <= d2);
//Console.WriteLine(d1);
//Console.WriteLine(d2);
TimeHelper.MeasureTime(() => SimulatedAnnealing.Calculate(10, 0.00001, options.OutputDirectory),
"solving tsp using simulated annealing");
}
Console.WriteLine($"\nJob done! Now it's time for tea. Total time elapsed: {stopWatch.Elapsed}");
Console.WriteLine(new Random().Next(0, 2) == 1
? "Лучший в СПбГУ - Факультет ПМ-ПУ"
: "Ответ на главный вопрос жизни, вселенной и всего такого - 42");
}
private void btnBest_Click(object sender, RoutedEventArgs e)
{
ClearLabels();
ClearClusters();
CalculateDistancesAndCreateAreas();
ClearLines();
List <int> bestOrder = new List <int>();
Dictionary <Cluster, double> lastDistances = new Dictionary <Cluster, double>();
Dictionary <Cluster, List <int> > bestOrders = new Dictionary <Cluster, List <int> >();
double lastDistance = double.MaxValue;
for (int i = 0; i < NrOfIterations; i++)
{
if (NrOfSalesmans <= 1)
{
List <int> order = annealingForOne.Calculate();
if (annealingForOne.CurrentDistance < lastDistance)
{
bestOrder = order;
}
}
else
{
foreach (Cluster clust in Clusters)
{
if (!lastDistances.ContainsKey(clust))
{
lastDistances.Add(clust, double.MaxValue);
}
if (!bestOrders.ContainsKey(clust))
{
bestOrders.Add(clust, new List <int>());
}
List <int> order = clust.Annealing.Calculate();
if (clust.Annealing.CurrentDistance < lastDistances[clust])
{
bestOrders[clust] = order;
}
}
}
}
if (NrOfSalesmans <= 1)
{
DrawLines(bestOrder);
txtBlockDistance.Text = String.Format("{0}", annealingForOne.CurrentDistance);
txtBlockMaxTime.Text = String.Format("{0}", annealingForOne.CurrentDistance);
}
else
{
double summedDistance = 0;
foreach (KeyValuePair <Cluster, List <int> > key in bestOrders)
{
DrawLines(key.Value, key.Key);
summedDistance += key.Key.Annealing.CurrentDistance;
}
txtBlockDistance.Text = String.Format("{0}", summedDistance);
txtBlockMaxTime.Text = String.Format("{0}", Clusters.Max(x => x.Annealing.CurrentDistance));
}
}