public Delta(DataMatrix data, SolutionMatrix solution)
{
ActualBestSolution = solution;
Data = data;
SwapCounter = 0;
ActualBestSolution.Score = Convert.ToInt32(RateSolution(solution.Solution.ToArray(), data));
CalculateDeltaTable();
}
public ActionResult MatrixGenerated(DataMatrix problem2, [FromQuery] string myMethod = null)
{
bool sym = true;
var problem = problem2;
for (int i = 0; i < problem.Dimension; i++)
{
for (int j = 0; j < problem.Dimension; j++)
{
if (problem.Distances[i][j] != problem.Distances[j][i])
{
sym = false;
}
}
}
for (int i = 0; i < problem.Dimension; i++)
{
for (int j = 0; j < problem.Dimension; j++)
{
if (problem.Flows[i][j] != problem.Flows[j][i])
{
sym = false;
}
}
}
if (sym != true)
{
return(RedirectToAction("Report"));
}
if (myMethod == "Greedy")
{
SolutionMatrix solution = new SolutionMatrix();
solution.SolutionArray = new int[problem.Flows.Count()];
var greedySolver = new GreedySolver(problem);
solution = greedySolver.GetSolution();
return(RedirectToAction("GreedySolutionGenerated", solution));
}
else if (myMethod == "Steepest")
{
SolutionMatrix solution = new SolutionMatrix();
solution.SolutionArray = new int[problem.Flows.Count()];
var steepestSolver = new SteepestSolver(problem);
solution.SolutionArray = steepestSolver.GetSolution().SolutionArray;
solution.Score = steepestSolver.GetSolution().Score;
return(RedirectToAction("SteepestSolutionGenerated", solution));
}
else
{
return(View(problem));
}
}
private void Finalise()
{
AssignmentMatrix = new Matrix(_m);
if (_isTransposed)
{
AssignmentMatrix = AssignmentMatrix.Transpose();
}
SolutionMatrix = AssignmentMatrix.MultiplyElements(CostMatrix);
TotalCost = SolutionMatrix.Sum();
if (IsShowDiagnostics)
{
ShowSolutionMatrix();
ShowTotalCost();
}
}
public ActionResult DataFile(IFormFile postedFile, [FromQuery] string myMethod = null)
{
_ = this.Environment.WebRootPath;
_ = this.Environment.ContentRootPath;
string path = Path.Combine(this.Environment.WebRootPath, "UploadedFiles");
if (!Directory.Exists(path))
{
Directory.CreateDirectory(path);
}
string fileName = Path.GetFileName(postedFile.FileName);
var problem = new DataMatrix();
using (var sr = new StreamReader(System.IO.File.OpenRead(Path.Combine(path, fileName))))
{
string data = sr.ReadToEnd();
var splitted = data.Split((char[])null, StringSplitOptions.RemoveEmptyEntries)
.ToList()
.Select(x => Convert.ToInt32(x))
.ToList();
int matrixSize = splitted[0];
problem.Dimension = matrixSize;
if (problem.Dimension != 0)
{
problem.Distances = new int[problem.Dimension][];
for (int i = 0; i < problem.Dimension; i++)
{
problem.Distances[i] = new int[problem.Dimension];
}
problem.Flows = new int[problem.Dimension][];
for (int i = 0; i < problem.Dimension; i++)
{
problem.Flows[i] = new int[problem.Dimension];
}
}
var qapDataFlow = new int[matrixSize][];
var qapDataDistance = new int[matrixSize][];
var chunked = splitted.Skip(1).Chunk(matrixSize).ToList();
for (int i = 0; i < matrixSize; ++i)
{
problem.Distances[i] = chunked[i].ToArray();
}
for (int i = matrixSize; i < 2 * matrixSize; ++i)
{
problem.Flows[i - matrixSize] = chunked[i].ToArray();
}
}
bool sym = true;
for (int i = 0; i < problem.Dimension; i++)
{
for (int j = 0; j < problem.Dimension; j++)
{
if (problem.Distances[i][j] != problem.Distances[j][i])
{
sym = false;
}
}
}
for (int i = 0; i < problem.Dimension; i++)
{
for (int j = 0; j < problem.Dimension; j++)
{
if (problem.Flows[i][j] != problem.Flows[j][i])
{
sym = false;
}
}
}
if (sym != true)
{
return(RedirectToAction("Report"));
}
var problemResult = new DataMatrix()
{
Dimension = problem.Dimension,
Distances = problem.Distances,
Flows = problem.Flows
};
if (myMethod == "Greedy")
{
SolutionMatrix solution = new SolutionMatrix();
solution.SolutionArray = new int[problem.Flows.Count()];
var greedySolver = new GreedySolver(problem);
solution = greedySolver.GetSolution();
return(RedirectToAction("GreedySolutionFile", solution));
}
else if (myMethod == "Steepest")
{
SolutionMatrix solution = new SolutionMatrix();
solution.SolutionArray = new int[problem.Flows.Count()];
var steepestSolver = new SteepestSolver(problem);
solution.SolutionArray = steepestSolver.GetSolution().SolutionArray;
solution.Score = steepestSolver.GetSolution().Score;
return(RedirectToAction("SteepestSolutionFile", solution));
}
else
{
return(View());
}
}
public ActionResult SteepestSolutionFile(SolutionMatrix solution)
{
return(View(solution));
}
public ActionResult GreedySolutionFile(SolutionMatrix solution)
{
return(View(solution));
}
public ActionResult SteepestSolutionGenerated(SolutionMatrix solution)
{
return(View(solution));
}
public ActionResult GreedySolutionGenerated(SolutionMatrix solution)
{
return(View(solution));
}
public override SolutionMatrix GetSolution()
{
var builder = new ConfigurationBuilder();
builder.SetBasePath(Directory.GetCurrentDirectory());
builder.AddJsonFile("appsettings.json");
var config = builder.Build();
string connectionString = config.GetConnectionString("DefaultConnection");
var optionsBuilder = new DbContextOptionsBuilder <AnaliticsContext>();
var options = optionsBuilder
.UseSqlServer(connectionString)
.Options;
AnaliticsContext db = new AnaliticsContext(options);
Stopwatch stopwatch = new Stopwatch();
SolutionMatrix solution = new SolutionMatrix
{
Dimension = Data.Distances.Length,
Solution = this.GetList(this.GetRandomInitSolution())
};
stopwatch.Start();
FirstSolution = solution.Solution.ToArray();
Delta betterSolution = new Delta(Data, solution);
CheckedElems = 0;
bool isLocalMinimum = false;
while (!isLocalMinimum)
{
if (!CheckBestNeighbor(betterSolution))
{
isLocalMinimum = true;
}
}
CheckedElems = Steps * Data.Dimension * (Data.Dimension - 1);
int score = 0;
for (int i = 1; i < solution.Solution.ToArray().Length; i++)
{
score += Data.Distances[solution.Solution.ToArray()[i - 1]][solution.Solution.ToArray()[i]] * Data.Flows[i - 1][i];
}
stopwatch.Stop();
var analitics = new Analitics();
analitics.Dimenssion = Data.Dimension;
long ticks = stopwatch.ElapsedTicks;
TimeSpan interval = TimeSpan.FromTicks(ticks);
analitics.Method = "Метод вектора спаду";
analitics.WorkTime = interval.ToString();
analitics.Score = score;
db.AnaliticsTable.Add(analitics);
db.SaveChangesAsync();
solution.Score = score;
solution.SolutionArray = betterSolution.ActualBestSolution.Solution.ToArray();
return(solution);
}
public override SolutionMatrix GetSolution()
{
var builder = new ConfigurationBuilder();
builder.SetBasePath(Directory.GetCurrentDirectory());
builder.AddJsonFile("appsettings.json");
var config = builder.Build();
string connectionString = config.GetConnectionString("DefaultConnection");
var optionsBuilder = new DbContextOptionsBuilder <AnaliticsContext>();
var options = optionsBuilder
.UseSqlServer(connectionString)
.Options;
AnaliticsContext db = new AnaliticsContext(options);
Stopwatch stopwatch = new Stopwatch();
var solutionMatrix = new SolutionMatrix();
int dimension_ = this.Data.Dimension;
var distancesPotential_ = new List <int>();
var flowPotential_ = new List <int>();
stopwatch.Start();
for (int i = 0; i < dimension_; ++i)
{
int potential = 0;
for (int j = 0; j < dimension_; ++j)
{
if (i != j)
{
potential += this.Data.Distances[i][j];
}
}
distancesPotential_.Add(potential);
}
for (int i = 0; i < dimension_; ++i)
{
int potential = 0;
for (int j = 0; j < dimension_; ++j)
{
if (i != j)
{
potential += this.Data.Flows[i][j];
}
}
flowPotential_.Add(potential);
}
int[] solution_ = Enumerable.Repeat(-1, Data.Dimension).ToArray();
for (int j = 0; j < dimension_; ++j)
{
int maxPos = 0;
int minPos = 0;
for (int i = 0; i < dimension_; ++i)
{
if (distancesPotential_[i] < distancesPotential_[maxPos])
{
maxPos = i;
}
if (flowPotential_[i] > flowPotential_[minPos])
{
minPos = i;
}
}
solution_[maxPos] = minPos;
distancesPotential_[maxPos] = -1;
flowPotential_[minPos] = Int32.MaxValue;
}
solutionMatrix.SolutionArray = solution_;
int score = 0;
for (int i = 1; i < solution_.Length; i++)
{
score += Data.Distances[solution_[i - 1]][solution_[i]] * Data.Flows[i - 1][i];
}
solutionMatrix.Score = score;
stopwatch.Stop();
var analitics = new Analitics();
analitics.Dimenssion = Data.Dimension;
long ticks = stopwatch.ElapsedTicks;
TimeSpan interval = TimeSpan.FromTicks(ticks);
analitics.Method = "Жадібний алгоритм";
analitics.WorkTime = interval.ToString();
analitics.Score = score;
db.AnaliticsTable.Add(analitics);
db.SaveChangesAsync();
return(solutionMatrix);
}