/// <summary>
/// Constructor.
/// </summary>
/// <param name="problem">The problem instance to solve.</param>
public DvrpSolver(DvrpProblem problem)
{
State = UCCTaskSolver.TaskSolver.TaskSolverState.OK;
_dvrpProblem = problem;
var n = _dvrpProblem.Requests.Length;
_distances = new double[n, n];
for (var i = 0; i < n; i++)
{
for (var j = i + 1; j < n; j++)
{
var dx = _dvrpProblem.Requests[i].X - _dvrpProblem.Requests[j].X;
var dy = _dvrpProblem.Requests[i].Y - _dvrpProblem.Requests[j].Y;
_distances[i, j] = _distances[j, i] = Math.Sqrt(dx*dx + dy*dy);
}
}
var m = _dvrpProblem.Depots.Length;
_depotDistances = new double[m, n];
for (var i = 0; i < m; i++)
{
for (var j = 0; j < n; j++)
{
var dx = _dvrpProblem.Depots[i].X - _dvrpProblem.Requests[j].X;
var dy = _dvrpProblem.Depots[i].Y - _dvrpProblem.Requests[j].Y;
_depotDistances[i, j] = Math.Sqrt(dx*dx + dy*dy);
}
}
_tspSolver = new TspSolver(this);
}
/// <summary>
/// Constructor.
/// </summary>
/// <param name="problem">The problem instance to solve.</param>
public DvrpSolver(DvrpProblem problem)
{
State = UCCTaskSolver.TaskSolver.TaskSolverState.OK;
_dvrpProblem = problem;
var n = _dvrpProblem.Requests.Length;
_distances = new double[n, n];
for (var i = 0; i < n; i++)
{
for (var j = i + 1; j < n; j++)
{
var dx = _dvrpProblem.Requests[i].X - _dvrpProblem.Requests[j].X;
var dy = _dvrpProblem.Requests[i].Y - _dvrpProblem.Requests[j].Y;
_distances[i, j] = _distances[j, i] = Math.Sqrt(dx * dx + dy * dy);
}
}
var m = _dvrpProblem.Depots.Length;
_depotDistances = new double[m, n];
for (var i = 0; i < m; i++)
{
for (var j = 0; j < n; j++)
{
var dx = _dvrpProblem.Depots[i].X - _dvrpProblem.Requests[j].X;
var dy = _dvrpProblem.Depots[i].Y - _dvrpProblem.Requests[j].Y;
_depotDistances[i, j] = Math.Sqrt(dx * dx + dy * dy);
}
}
_tspSolver = new TspSolver(this);
}
private static void RunRandomLSPathsStatistics(IGraph graph, TspSolver solver, string coordinatesPath)
{
var localSearchSolver = new PathSimilaritySolver(graph, new InitializationSolver(solver,
new RandomPathAlgorithm(Steps, new EdgeFinder())),
new ISimilarityCalculationStrategy[] { new EdgeSimillarityStrategy(), new NodeSimilarityStrategy() });
var localSearchAlgorithm = new LocalSearchAlgorithm(Steps, new EdgeFinder());
localSearchSolver.Solve(localSearchAlgorithm);
}
private static void RunBasicAlgorithms(TspSolver solver, string coordinatesPath, string resultsPath)
{
var resultPrinter = new ResultPrinter()
.AddPrinter(new ConsolePrinter(), new ConsoleContentBuilder(solver.SolvingStatistics))
.AddPrinter(new FilePrinter(resultsPath, $"{DateTime.Now.Date.ToFileTime()}_results.txt"),
new FileContentBuilder(solver.SolvingStatistics, coordinatesPath));
SolveAndPrint(solver, new NearestNeighborAlgorithm(Steps, new EdgeFinder()), "NEAREST NEIGHBOR", resultPrinter);
SolveAndPrint(solver, new GreedyCycleAlgorithm(Steps, new EdgeFinder()), "GREEDY CYCLE", resultPrinter);
SolveAndPrint(solver, new NearestNeighborAlgorithm(Steps, new GraspEdgeFinder(3)), "NEAREST NEIGHBOR GRASP", resultPrinter);
SolveAndPrint(solver, new GreedyCycleAlgorithm(Steps, new GraspEdgeFinder(3)), "GREEDY CYCLE GRASP", resultPrinter);
}
private static void RunILSAlgorithm(IGraph graph, TspSolver solver, string coordinatesPath, string resultsPath)
{
var localSearchSolver = new TspIteratedLocalSearchSolver(graph, solver, new NearestNeighborAlgorithm(Steps, new GraspEdgeFinder(3)));
var localSearchAlgorithm = new LocalSearchAlgorithm(Steps, new EdgeFinder());
SolveAndPrint(localSearchSolver, localSearchAlgorithm,
"NN Grasp with local search (ILS)", LocalSearchResultPrinter(localSearchSolver, "NNG_ILS", coordinatesPath, resultsPath));
localSearchSolver = new TspIteratedLocalSearchSolver(graph, solver, new GreedyCycleAlgorithm(Steps, new GraspEdgeFinder(3)));
localSearchAlgorithm = new LocalSearchAlgorithm(Steps, new EdgeFinder());
SolveAndPrint(localSearchSolver, localSearchAlgorithm,
"GC Grasp with local search (ILS)", LocalSearchResultPrinter(localSearchSolver, "GCG_ILS", coordinatesPath, resultsPath));
localSearchSolver = new TspIteratedLocalSearchSolver(graph, solver, new RandomPathAlgorithm(Steps, new EdgeFinder()));
localSearchAlgorithm = new LocalSearchAlgorithm(Steps, new EdgeFinder());
SolveAndPrint(localSearchSolver, localSearchAlgorithm,
"Random with local search (ILS)", LocalSearchResultPrinter(localSearchSolver, "Random_ILS", coordinatesPath, resultsPath));
}
public static void Main(string[] args)
{
var buildConfig = BuildConfiguration();
var config = buildConfig.GetSection(nameof(AppConfiguration));
var dataPath = config["data"];
var resultPath = config["results"];
var graphEdges = System.IO.Path.Combine(dataPath, config["graphEdges"]);
var graphCoordinates = System.IO.Path.Combine(dataPath, config["graphCoordinates"]);
var dataLoader = new GraphLoader(graphEdges, 100);
var graph = dataLoader.Load();
var calculationStrategies = new ISimilarityCalculationStrategy[]
{ new EdgeSimillarityStrategy(), new NodeSimilarityStrategy() };
var simpleSolver = new TspSolver(graph);
var localSearchSolver = new TspLocalSearchSolver(graph);
var edgeFinder = new GraspEdgeFinder(3);
var evolutinarySolver = new EvolutionarySolver(graph,
new Recombinator(new SimilarityFinder(calculationStrategies), Steps, graph),
new Selector(), 41000);
var localSearch = new LocalSearchAlgorithm(Steps, edgeFinder);
var stats = new BasicSolverStatistics();
var bestCost = int.MaxValue;
ISolverStatistics bestStatistics = new BasicSolverStatistics();
for (var i = 0; i < 10; i++)
{
var generatedPaths = simpleSolver.Solve(new RandomPathAlgorithm(Steps, edgeFinder));
generatedPaths = localSearchSolver.Solve(localSearch, generatedPaths);
evolutinarySolver.Solve(localSearch, generatedPaths);
if (evolutinarySolver.SolvingStatistics.BestPath.Cost < bestCost)
{
bestCost = evolutinarySolver.SolvingStatistics.BestPath.Cost;
bestStatistics = evolutinarySolver.SolvingStatistics;
}
stats.UpdateSolvingResults(evolutinarySolver.SolvingStatistics.BestPath, evolutinarySolver.SolvingStatistics.MeanSolvingTime);
}
var statsPrinter = new FilePrinter(resultPath, "evo_stats.res");
statsPrinter.Print(stats.ToString());
var output = new StringBuilder();
output.AppendLine($"{"Id".PadRight(4)}\tCost\tTime");
for (var i = 0; i < bestStatistics.Costs.Count; i++)
{
output.AppendLine($"{i.ToString().PadRight(4)}\t{bestStatistics.Costs[i].ToString().PadRight(4)}\t{bestStatistics.SolvingTimes[i].Milliseconds:D}");
}
var evoResultsPrinter = new FilePrinter(resultPath, "evolutionary_results.res");
evoResultsPrinter.Print(output.ToString());
Console.WriteLine("Evolutionary solver ended his work!");
//SimilaritySolver(resultPath, graph, calculationStrategies, edgeFinder);
}
public static void Main(string[] args)
{
#region MyRegion
/* new Node("f", 0, 9),
* new Node("g", 1, 4),
* new Node("h", 1, 6),
* new Node("i", 3, 4),
* new Node("j", 8, 4),
* new Node("k", 9, 4),
* new Node("l", 4, 4)
*
*/
#endregion
var xxxx = new List <Node>
{
new Node("A", 0, 0),
new Node("B", 1, 1),
new Node("C", 2, 2),
new Node("D", 2, 9),
new Node("E", 4, 5),
new Node("F", 8, 1),
};
#region mockList
//var A = new Node("A", 1, 1);
//var B = new Node("B", 1, 1);
//var C = new Node("C", 1, 1);
//var D = new Node("D", 1, 1);
//var E = new Node("E", 1, 1);
//A.Routes = new Dictionary<Node, Route>()
//{
// {A, new Route(0)},
// {B, new Route(10)},
// {C, new Route(12)},
// {D, new Route(11)},
// {E, new Route(14)},
//};
//B.Routes = new Dictionary<Node, Route>()
//{
// {A, new Route(10)},
// {B, new Route(0)},
// {C, new Route(13)},
// {D, new Route(15)},
// {E, new Route(18)},
//};
//C.Routes = new Dictionary<Node, Route>()
//{
// {A, new Route(12)},
// {B, new Route(13)},
// {C, new Route(0)},
// {D, new Route(9)},
// {E, new Route(14)},
//};
//D.Routes = new Dictionary<Node, Route>()
//{
// {A, new Route(11)},
// {B, new Route(15)},
// {C, new Route(9)},
// {D, new Route(0)},
// {E, new Route(16)},
//};
//E.Routes = new Dictionary<Node, Route>()
//{
// {A, new Route(14)},
// {B, new Route(8)},
// {C, new Route(14)},
// {D, new Route(16)},
// {E, new Route(0)},
//};
//var mockNodes = new List<Node> {A, B, C, D, E};
#endregion
//TspSolver
// .AntColonyOptimization()
// .Default()
// .WithCities(xxxx)
// .StartFrom(1)
// .WithAnts(6)
// .WithMaximumTime(1000)
// .Solve();
TspSolver
.AntColonyOptimization()
.Custom()
.WithInfluenceOfPheromoneOnDrection(2)
.WithInfluenceOfAdjacentNodeDistance(3)
.WithPheromoneDecreaseFactor(0.1)
.WithPheromoneIncreaseFactor(3)
.WithCities(xxxx /*@"C:\Users\dariusz.dabrowski\Desktop\Ceneo\Nodes.txt"*/)
.StartFromRandomPosition()
.WithAnts(2)
.WithMaximumTime(10000)
.Solve();
Console.ReadKey();
}
