public List <MultiResult> Run()
{
StartLogging();
if (FixedTimeSlotAssignments != null)
{
Console.WriteLine("Fixing timeslots");
_model.SetAndFixSolution(FixedTimeSlotAssignments);
}
double minCost;
int maxSoftConsViol;
int minSoftConsViol;
double maxCost;
int costBound;
int softObjBound;
CalculateCornerPoints(_multiResults, out minCost, out maxCost, out maxSoftConsViol, out minSoftConsViol, out costBound, out softObjBound);
Console.WriteLine($"Slope between corners: {(maxCost-minCost)/(maxSoftConsViol-minSoftConsViol) : #.##}\nPenalty: {_model.ModelParameters.ConstraintPenalty}");
var pareto = GetParetoPoints(_multiResults);
if (Math.Abs(minCost - maxCost) < 0.05)
{
Console.WriteLine("Only one solution found. Returning");
return(pareto);
}
if (UseEpsilonMethod)
{
RunEpsilonMethod(minSoftConsViol, maxSoftConsViol, minCost, maxCost);
}
else
{
RunWieghtedSumMetod(minSoftConsViol, maxSoftConsViol, minCost, maxCost);
}
_stopwatch.Stop();
//todo: refactor this in to its own function.
Console.WriteLine($"Elapsed time: {_stopwatch.Elapsed} -- {_stopwatch.ElapsedMilliseconds}ms");
pareto = GetParetoPoints(_multiResults);
Console.WriteLine($"\nBounds:\nCost: {costBound}\nSoftObj: {softObjBound}\n");
DisplaySolutions(pareto);
DisplayRoomProfiles(pareto);
DisplayTimeSlots(pareto);
DisplayChanges(pareto);
return(pareto);
}
public Solution SolveStageII()
{
var model = new CCTModel(data, formulation, new CCTModel.MIPModelParameters()
{
UseStageIandII = true,
});
model.SetAndFixSolution(_solution._assignments.ToList());
//model.MipStart(_solution._assignments.ToList());
model.Optimize(1200);
_solution.SetAssignments(model.GetAssignments());
return(_solution);
}
public void TestSolutionread()
{
var data = Data.ReadXml(dataPath + ITC_Comp01, "120", "4");
var formulation = ProblemFormulation.UD2;
var sol = new Solution(data, formulation);
sol.Read(dataPath + @"ITC2007\sol\comp01-UD2.sol");
sol.AnalyzeSolution();
Assert.AreEqual(0, sol.UnscheduledLectures);
var model = new CCTModel(data, ProblemFormulation.UD2);
model.SetAndFixSolution(sol._assignments.ToList());
model.Optimize();
Assert.AreEqual(5, model.Objective);
}
public void TopSolutionsAnalysis(string filename)
{
var name = Path.GetFileNameWithoutExtension(filename);
var data = Data.ReadXml(dataPath + filename, "120", "4");
var formulation = ProblemFormulation.UD2NoOverbook;
var courestime = new Dictionary <Course, Dictionary <TimeSlot, int> >();
var penaltyforcourse = new Dictionary <Course, int>();
foreach (var course in data.Courses)
{
courestime.Add(course, new Dictionary <TimeSlot, int>());
foreach (var timeSlot in data.TimeSlots)
{
courestime[course].Add(timeSlot, 0);
}
penaltyforcourse[course] = 0;
}
var bestsol = new List <Assignment>();
var penMWD = new List <int>();
var penCC = new List <int>();
for (var i = 0; i < 10; i++)
{
var sol = new Solution(data, formulation);
sol.Read(dataPath + @"ITC2007\sol\" + name + "-UD2-" + i + ".sol");
sol.AnalyzeSolution();
foreach (var assignment in sol._assignments)
{
courestime[assignment.Course][assignment.TimeSlot]++;
}
foreach (var course in data.Courses)
{
penaltyforcourse[course] += sol.PenaltyForCourse[course];
}
penMWD.Add((int)sol.MinimumWorkingDays);
penCC.Add((int)sol.CurriculumCompactness);
if (i == 0)
{
bestsol = sol._assignments.ToList();
}
}
const int minhint = 7;
var maxhint = 7;
var noise = 0.5;
const bool fixhints = true;
var random = new Random(62);
foreach (var course in data.Courses)
{
foreach (var ts in data.TimeSlots)
{
// if (random.Next(10) < courestime[course][ts]) courestime[course][ts] = 1;
// else courestime[course][ts] = 0;
if (courestime[course][ts] < minhint)
{
courestime[course][ts] = 0;
}
if (courestime[course][ts] > maxhint)
{
courestime[course][ts] = 0;
}
//result should be made to double.
// if(courestime[course][ts] > 0) courestime[course][ts] += random.Next(-3,3);
//courestime[course][ts] *= 1 + (int) Math.Round(noise*(2*random.NextDouble()-1));
}
}
var hints = courestime.SelectMany(c => c.Value.Where(cv => cv.Value > 0).Select(cv => Tuple.Create(c.Key, cv.Key, cv.Value))).ToList();
var currtime = new Dictionary <Curriculum, Dictionary <TimeSlot, int> >();
foreach (var curr in data.Curricula)
{
currtime.Add(curr, new Dictionary <TimeSlot, int>());
foreach (var timeSlot in data.TimeSlots)
{
currtime[curr].Add(timeSlot, courestime.Where(c => curr.Courses.Contains(c.Key)).Sum(kv => kv.Value[timeSlot]));
}
}
var chints = currtime.SelectMany(c => c.Value.Select(cv => Tuple.Create(c.Key, cv.Key, cv.Value))).ToList();
Console.WriteLine($"Timeslots: {data.TimeSlots.Count}");
Console.WriteLine($"MWD: avg: {penMWD.Average()} - {string.Join(", ", penMWD)} ");
Console.WriteLine($"CC: avg: {penCC.Average()} - {string.Join(", ", penCC)} ");
foreach (var course in data.Courses.OrderByDescending(c => penaltyforcourse[c]))
{
Console.WriteLine($"\nCourse: {course}\n" +
$"Size: {course.NumberOfStudents}\n" +
$"Lectures: {course.Lectures}\n" +
$"MWD: {course.MinimumWorkingDays}\n" +
$"TSAvaialble:{data.TimeSlots.Count - course.UnavailableTimeSlots.Count}\n" +
$"Unavail: {string.Join(",", course.UnavailableTimeSlots)}\n" +
$"TotalPenalty: {penaltyforcourse[course]}");
foreach (var valuePair in courestime[course].Where(kv => kv.Value > 0).OrderByDescending(kv => kv.Value))
{
Console.WriteLine(valuePair.Key + ": " + valuePair.Value);
}
}
Console.WriteLine("\n\nBy prio: ");
foreach (var hint in hints.Where(h => h.Item3 > 0).OrderByDescending(h => h.Item3))
{
Console.WriteLine(hint.Item1.ID + "_" + hint.Item2 + ": " + hint.Item3);
}
Console.WriteLine("\n\nHistogram: ");
Console.WriteLine("total lectures: " + data.Courses.Sum(c => c.Lectures));
for (var i = 1; i <= 10; i++)
{
Console.WriteLine($"{i}\t{hints.Count(h => h.Item3 == i)}");
}
Console.WriteLine("Unavailabilites\tSame");
foreach (var course in data.Courses)
{
Console.WriteLine($"{course.UnavailableTimeSlots.Count}\t{(double) courestime[course].Sum(t => t.Value)/course.Lectures : 0.00}");
}
Console.WriteLine("Penal\tSame");
foreach (var course in data.Courses)
{
Console.WriteLine($"{penaltyforcourse[course]}\t{(double) courestime[course].Sum(t => t.Value)/course.Lectures : 0.00}");
}
Console.WriteLine("Size\tSame");
foreach (var course in data.Courses)
{
Console.WriteLine($"{course.NumberOfStudents}\t{(double) courestime[course].Sum(t => t.Value)/course.Lectures : 0.00}");
}
// return;
//Console.WriteLine("\n\nCurriculumPatterns");
//foreach (var hint in chints.Where(h => h.Item3 > 0).OrderByDescending(h => h.Item3))
//{
// Console.WriteLine(hint.Item1.ID + "_" + hint.Item2 + ": " + hint.Item3);
//}
//Console.WriteLine("\n\nHistogram: ");
//Console.WriteLine("total curr_lectures: " + data.Curricula.Sum(c => c.Lectures));
//for (var i = 1; i <= 10; i++)
//{
// Console.WriteLine($"{i}\t{chints.Count(h => h.Item3 == i)}");
//}
var ModelParameters = new CCTModel.MIPModelParameters()
{
UseStageIandII = false,
TuneGurobi = true,
UseHallsConditions = true,
UseRoomHallConditions = true,
// Seed = seeds[i],
};
var model = new CCTModel(data, formulation, ModelParameters);
// model.SetMipHints(chints);
Console.WriteLine($"Adding {hints.Count} hints. Total letures: {data.Courses.Sum(c => c.Lectures)} ({(double) hints.Count / data.Courses.Sum(c => c.Lectures) :0.00%})");
model.SetMipHints(hints, fixhints);
// model.MipStart(bestsol);
var r = model.Optimize(300);
// model.Optimize(60*60*3);
var ass = model.GetAssignments();
var finalsol = new Solution(data, formulation);
finalsol.SetAssignments(ass);
finalsol.Save(@"C:\temp\finalsolStageI_" + name + ".sol");
var ModelParameters2 = new CCTModel.MIPModelParameters()
{
UseStageIandII = true,
TuneGurobi = true,
UseHallsConditions = true,
UseRoomHallConditions = true,
// Seed = seeds[i],
};
var model2 = new CCTModel(data, formulation, ModelParameters2);
model2.SetAndFixSolution(ass);
model2.Optimize(300);
ass = model2.GetAssignments();
finalsol.SetAssignments(ass);
finalsol.Save(@"C:\temp\finalsolStageII_" + name + ".sol");
}
