public void TestProximityConstraint()
{
// var data = Data.ReadXml(dataPath + Erlangen2012_1, "120", "4");
var data = Data.ReadXml(dataPath + ITC_Comp05, "120", "4");
// var formulation = ProblemFormulation.UD2;
//Formulation.AvailabilityHardConstraint = false;
//Formulation.OverbookingAllowed = 0.35;
var ModelParameters = new CCTModel.MIPModelParameters()
{
UseStageIandII = false,
ConstraintPenalty = 50,
AbortSolverOnZeroPenalty = true,
};
var model = new CCTModel(data, formulation, ModelParameters);
var watch = Stopwatch.StartNew();
model.Optimize(30, 0.99);
var obj = model.ObjSoftCons;
model.SetObjective(0, 0, 1);
while (watch.Elapsed.TotalSeconds < TimelimitStageI)
{
model.SetProximityOrigin(true);
model.SetQualConstraint(obj - 10);
model.Optimize(15);
obj = model.ObjSoftCons;
Console.WriteLine($"Objective: {obj}");
}
}
public QualityRecoveringOptimizer(Data data, Solution solutionBefore, ProblemFormulation formulation, CCTModel.MIPModelParameters mipModelParameters)
{
this.data = data;
this.formulation = formulation;
this.MIPmodelParameters = mipModelParameters;
this.solutionBefore = solutionBefore;
model = new CCTModel(data, formulation, MIPmodelParameters);
model.SetProximityOrigin(solutionBefore._assignments.ToList());
model.SetMipHints(solutionBefore._assignments.ToList());
}
public Solution Run()
{
var stopwatch = Stopwatch.StartNew();
var model = new CCTModel(data, formulation, MIPmodelParameters);
model.Optimize(TimelimitStageI - Timetotighten);
var userooms = model.GetUsedRooms();
Console.WriteLine($"Used rooms: {userooms.Sum(kv => kv.Value)} over {userooms.Count} ");
Console.WriteLine($"OveruseOnTimeslots: {model.GetOverUseOfRooms()} ");
// model.PenalizeRoomUsedMoreThanOnce(100);
model.PenalizeRoomUsedMoreThanOnce(10, true);
model.SetObjective(0, 0, 0.01);
//model.SetObjective(0, 0, 0);
//model.SetMipHintToCurrent();
model.SetProximityOrigin();
model.SetQualConstraint(model.ObjSoftCons);
model.Fixsol(true);
model.Optimize();
model.Fixsol(false);
// model.Optimize(timetotighten+50,cutoff:500);
model.ModelParameters.AbortSolverOnZeroPenalty = true;
var tighttimer = Stopwatch.StartNew();
model.Optimize(Timetotighten + 300);
tighttimer.Stop();
model.DisplayObjectives();
_solution = new Solution(data, formulation);
_solution.SetAssignments(model.GetAssignments());
//timers
stopwatch.Stop();
tighttimer.Stop();
totalseconds = (int)stopwatch.Elapsed.TotalSeconds;
roomtightseconds = (int)tighttimer.Elapsed.TotalSeconds;
return(_solution);
}
public Solution RunUnavailbility()
{
var stopwatch = Stopwatch.StartNew();
var model = new CCTModel(data, formulation, MIPmodelParameters);
model.Optimize(TimelimitStageI - Timetotighten);
Console.WriteLine($"Unavailableused: {model.GetUnavailableused()} ({(double) model.GetUnavailableused()/data.Courses.Sum(c => c.Lectures):0.00%})");
model.PenalizeUnavailability(10);
// model.SetObjective(0, 0, 0.01);
// model.SetObjective(0, 0, 0);
//model.SetMipHintToCurrent();
model.SetProximityOrigin();
// model.SetQualConstraint(model.ObjSoftCons);
model.Fixsol(true);
model.Optimize();
model.Fixsol(false);
// model.Optimize(timetotighten+50,cutoff:500);
// model.ModelParameters.AbortSolverOnZeroPenalty = true;
var tighttimer = Stopwatch.StartNew();
model.Optimize(Timetotighten + 900);
tighttimer.Stop();
model.DisplayObjectives();
_solution = new Solution(data, formulation);
_solution.SetAssignments(model.GetAssignments());
Console.WriteLine($"Unavailableused: {model.GetUnavailableused()} ({(double)model.GetUnavailableused() / data.Courses.Sum(c => c.Lectures):0.00%})");
//timers
stopwatch.Stop();
tighttimer.Stop();
totalseconds = (int)stopwatch.Elapsed.TotalSeconds;
roomtightseconds = (int)tighttimer.Elapsed.TotalSeconds;
return(_solution);
}
public void TestLocalBranchingConstraint(bool usecurr, int N)
{
var data = Data.ReadXml(dataPath + ITC_Comp05, "120", "4");
//var formulation = ProblemFormulation.UD2;
//Formulation.AvailabilityHardConstraint = false;
//Formulation.OverbookingAllowed = 0.35;
var modelParameters = new CCTModel.MIPModelParameters()
{
UseStageIandII = false
};
var model = new CCTModel(data, formulation, modelParameters);
model.Optimize(30 * 3, 0.99);
model.SetProxConstraint(N);
var watch = Stopwatch.StartNew();
while (watch.Elapsed.TotalSeconds < TimelimitStageI)
{
model.SetProximityOrigin(usecurr);
model.Optimize(15);
}
}
private void OptimizeSubProblem(int minSoftConsViol, int maxSoftConsViol, double minCost, double maxCost, double alpha)
{
StartLogging();
double?qual = null;
double?budget = null;
if (EpsilonOnQuality)
{
qual = Math.Floor(minSoftConsViol * (1 - alpha) + maxSoftConsViol * alpha);
_model.SetQualConstraint((int?)Math.Floor((double)qual));
Console.WriteLine($"Alpha: {alpha:0.00} QualConstraint: {qual}");
}
else
{
budget = minCost * (1 - alpha) + maxCost * alpha;
_model.SetBudgetConstraint(budget);
Console.WriteLine($"Alpha: {alpha:0.00} BudgetConstraint: {budget}");
}
/*
* a weighting scheme
* model.SetObjective(alpha* minRoomCost, (1-alpha)* minQual);
*/
if (LocalBranching > 0)
{
_model.SetProximityOrigin();
}
_model.Optimize(Timelimit, MIPGap);
Console.WriteLine($"LastSolution:\n(cost,softobj) = {_model.ObjCost} , {_model.ObjSoftCons}");
int?costBound = EpsilonOnQuality ?(int?)Math.Ceiling(_model.ObjBound) : null;
int?softobjBound = !EpsilonOnQuality ? (int?)Math.Ceiling(_model.ObjBound) : null;
_multiResults.Add(new MultiResult(_model.ObjCost, _model.ObjSoftCons, costBound, softobjBound, _model.GetUsedRooms(),
_model.GetAssignments(), budget, qual, (int)_stopwatch.Elapsed.TotalSeconds));
AddAllSolutions(_model);
}
// [TestCase(ITC_Comp05,1)]
/*
* [TestCase(ITC_Comp05, 2)]
* [TestCase(ITC_Comp05, 3)]
* [TestCase(ITC_Comp05, 4)]
* [TestCase(ITC_Comp05, 5)]
* [TestCase(ITC_Comp05, 6)]
* [TestCase(ITC_Comp05, 7)]
* [TestCase(ITC_Comp05, 8)]
* [TestCase(ITC_Comp05, 11)]
* [TestCase(ITC_Comp05, 12)]
* [TestCase(ITC_Comp05, 13)]
* [TestCase(ITC_Comp05, 14)]
* [TestCase(ITC_Comp05, 15)]
* [TestCase(ITC_Comp05, 16)]
* [TestCase(ITC_Comp05, 17)]
*/
public void CCfirstHeuristic30s(string filename, int seed) //
{
// var seed = 0;
for (int ia = 1; ia < 5; ia++)
{
seed = ia;
var data = Data.ReadXml(dataPath + filename, "120", "4");
// var newrooms = CreateRooms(data);
// data.SetRoomList(newrooms);
var problemFormulation = ProblemFormulation.UD2NoOverbook;
problemFormulation.MinimumWorkingDaysWeight = 0;
// problemFormulation.CurriculumCompactnessWeight = 0;
var par = new CCTModel.MIPModelParameters()
{
TuneGurobi = true,
UseStageIandII = false,
UseHallsConditions = true,
UseRoomHallConditions = true,
UseRoomsAsTypes = false,
Seed = seed,
};
var model = new CCTModel(data, problemFormulation, par);
model.SetObjective(1, 0, 0);
model.Optimize(TimelimitStageI);
model.DisplayObjectives();
var result = new Dictionary <double, double>();
//maybe find better proximity that reflects currciulumcompactness better.
//Check which curriculum that can be moved without introducting penalties.
model.SetProximityOrigin(true);
problemFormulation.MinimumWorkingDaysWeight = 5;
for (var i = 15; i <= 15; i++)
{
// model.SetObjective(0, 0, i);
model.SetProxConstraint(i);
model.AddMinimumWorkingDaysCost();
// model.FixCurricula(true);
model.Optimize();
model.DisplayObjectives();
model.SetObjective(1, 0, 0);
model.Fixsol(true);
model.Optimize();
model.Fixsol(false);
model.DisplayObjectives();
result[i] = model.Objective;
}
Console.WriteLine("Results:");
Console.WriteLine("i;obj");
foreach (var r in result)
{
Console.WriteLine($"{r.Key};{r.Value}");
}
var best = result.Min(r => r.Value);
File.AppendAllText(@"c:\temp\heuristic.txt", $"{nameof(CCfirstHeuristic30s)};{filename};{best}\n");
// model.FixCurricula(false);
// maybe also save multiple minimum curriculum solutions
}
}
public void Lex_soft_cost_withTimeslot(string filename)
{
var algname = nameof(Lex_soft_cost_withTimeslot);
// formulation.AvailabilityHardConstraint = false;
var data = Data.ReadXml(dataPath + filename, "120", "4");
var newrooms = CreateRoomsFixedSize(data, 25, 5);
data.SetRoomList(newrooms);
var par = new CCTModel.MIPModelParameters()
{
UseStageIandII = false,
UseHallsConditions = true,
UseRoomHallConditions = true,
TuneGurobi = false,
UseRoomsAsTypes = false,
};
var costmodel = new CCTModel(data, ProblemFormulation.MinimizeRoomCost, par);
costmodel.Optimize();
data.SetRoomList(costmodel.GetUsedRooms().Where(kv => kv.Value > 0).Select(kv => kv.Key).ToList());
//var formulation = ProblemFormulation.UD2NoOverbook;
// formulation.AvailabilityHardConstraint = false;
// formulation.OverbookingAllowed = 0.35;
var ModelParameters = new CCTModel.MIPModelParameters()
{
UseStageIandII = false,
TuneGurobi = true,
UseHallsConditions = true,
UseRoomHallConditions = true,
// UseRoomsAsTypes = true,
UseRoomsAsTypes = false,
RoomBoundForEachTimeSlot = true,
};
var model = new CCTModel(data, _problemFormulation, ModelParameters);
model.Optimize(300);
var userooms = model.GetUsedRooms();
Console.WriteLine($"Used rooms: {userooms.Sum(kv => kv.Value)} over {userooms.Count} ");
// model.PenalizeRoomUsedMoreThanOnce(100);
model.PenalizeRoomUsedMoreThanOnce(1, true);
model.SetObjective(0, 0, 0.001);
model.SetProximityOrigin();
model.SetQualConstraint(model.ObjSoftCons);
// model.SetProxConstraint(20);
model.Fixsol(true);
model.Optimize();
model.Fixsol(false);
model.Optimize(900);
model.DisplayObjectives();
var sol = new Solution(data, ProblemFormulation.MinimizeRoomCost);
sol.SetAssignments(model.GetAssignments());
Console.WriteLine(sol.AnalyzeSolution());
File.AppendAllText(@"c:\temp\heuristic.txt", $"{algname};{filename};{model.ObjSoftCons}\n");
}