public void StandGrowthPerformance()
{
int thinningPeriod = 4;
int runs = 4; // 1 warmup run + measured runs
int trees = 300;
#if DEBUG
runs = 1; // do only functional validation of test on DEBUG builds to reduce test execution time
trees = 10;
#endif
PlotsWithHeight nelder = PublicApi.GetNelder();
OrganonConfiguration configuration = PublicApi.CreateOrganonConfiguration(new OrganonVariantNwo());
configuration.Treatments.Harvests.Add(new ThinByIndividualTreeSelection(thinningPeriod));
OrganonStand stand = nelder.ToOrganonStand(configuration, 20, 130.0F, trees);
stand.PlantingDensityInTreesPerHectare = TestConstant.NelderReplantingDensityInTreesPerHectare;
Objective landExpectationValue = new Objective()
{
IsLandExpectationValue = true,
PlanningPeriods = 9
};
HeuristicParameters defaultParameters = new HeuristicParameters();
TimeSpan runtime = TimeSpan.Zero;
for (int run = 0; run < runs; ++run)
{
// after warmup: 3 runs * 300 trees = 900 measured growth simulations on i7-3770 (4th gen, Sandy Bridge)
// dispersion of 5 runs min mean median max
// .NET 5.0 with removed tree compaction 1.67 1.72 1.72 1.82
Hero hero = new Hero(stand, configuration, landExpectationValue, defaultParameters)
{
IsStochastic = false,
MaximumIterations = 2
};
hero.RandomizeTreeSelection(TestConstant.Default.SelectionPercentage);
if (run > 0)
{
// skip first run as a warmup run
runtime += hero.Run();
}
}
this.TestContext !.WriteLine(runtime.TotalSeconds.ToString());
}
public void NelderOtherHeuristics()
{
int thinningPeriod = 4;
int treeCount = 75;
#if DEBUG
treeCount = 25;
#endif
PlotsWithHeight nelder = PublicApi.GetNelder();
OrganonConfiguration configuration = OrganonTest.CreateOrganonConfiguration(new OrganonVariantNwo());
configuration.Treatments.Harvests.Add(new ThinByIndividualTreeSelection(thinningPeriod));
OrganonStand stand = nelder.ToOrganonStand(configuration, 20, 130.0F, treeCount);
stand.PlantingDensityInTreesPerHectare = TestConstant.NelderReplantingDensityInTreesPerHectare;
Objective landExpectationValue = new Objective()
{
IsLandExpectationValue = true,
PlanningPeriods = 9
};
Objective volume = new Objective()
{
PlanningPeriods = landExpectationValue.PlanningPeriods
};
HeuristicParameters defaultParameters = new HeuristicParameters()
{
UseScaledVolume = false
};
GeneticParameters geneticParameters = new GeneticParameters(treeCount)
{
PopulationSize = 7,
MaximumGenerations = 5,
UseScaledVolume = defaultParameters.UseScaledVolume
};
GeneticAlgorithm genetic = new GeneticAlgorithm(stand, configuration, landExpectationValue, geneticParameters);
TimeSpan geneticRuntime = genetic.Run();
GreatDeluge deluge = new GreatDeluge(stand, configuration, volume, defaultParameters)
{
RainRate = 5,
LowerWaterAfter = 9,
StopAfter = 10
};
deluge.RandomizeTreeSelection(TestConstant.Default.SelectionPercentage);
TimeSpan delugeRuntime = deluge.Run();
RecordTravel recordTravel = new RecordTravel(stand, configuration, landExpectationValue, defaultParameters)
{
StopAfter = 10
};
recordTravel.RandomizeTreeSelection(TestConstant.Default.SelectionPercentage);
TimeSpan recordRuntime = recordTravel.Run();
SimulatedAnnealing annealer = new SimulatedAnnealing(stand, configuration, volume, defaultParameters)
{
Iterations = 100
};
annealer.RandomizeTreeSelection(TestConstant.Default.SelectionPercentage);
TimeSpan annealerRuntime = annealer.Run();
TabuParameters tabuParameters = new TabuParameters()
{
UseScaledVolume = defaultParameters.UseScaledVolume
};
TabuSearch tabu = new TabuSearch(stand, configuration, landExpectationValue, tabuParameters)
{
Iterations = 7,
//Jump = 2,
MaximumTenure = 5
};
tabu.RandomizeTreeSelection(TestConstant.Default.SelectionPercentage);
TimeSpan tabuRuntime = tabu.Run();
ThresholdAccepting thresholdAcceptor = new ThresholdAccepting(stand, configuration, volume, defaultParameters);
thresholdAcceptor.IterationsPerThreshold.Clear();
thresholdAcceptor.Thresholds.Clear();
thresholdAcceptor.IterationsPerThreshold.Add(10);
thresholdAcceptor.Thresholds.Add(1.0F);
thresholdAcceptor.RandomizeTreeSelection(TestConstant.Default.SelectionPercentage);
TimeSpan acceptorRuntime = thresholdAcceptor.Run();
RandomGuessing random = new RandomGuessing(stand, configuration, volume, defaultParameters)
{
Iterations = 4
};
TimeSpan randomRuntime = random.Run();
configuration.Treatments.Harvests.Clear();
configuration.Treatments.Harvests.Add(new ThinByPrescription(thinningPeriod));
PrescriptionParameters prescriptionParameters = new PrescriptionParameters()
{
Maximum = 60.0F,
Minimum = 50.0F,
Step = 10.0F,
UseScaledVolume = defaultParameters.UseScaledVolume
};
PrescriptionEnumeration enumerator = new PrescriptionEnumeration(stand, configuration, landExpectationValue, prescriptionParameters);
TimeSpan enumerationRuntime = enumerator.Run();
// heuristics assigned to volume optimization
this.Verify(deluge);
this.Verify(annealer);
this.Verify(thresholdAcceptor);
this.Verify(random);
// heuristics assigned to net present value optimization
this.Verify(genetic);
this.Verify(enumerator);
this.Verify(recordTravel);
this.Verify(tabu);
HeuristicSolutionDistribution distribution = new HeuristicSolutionDistribution(1, thinningPeriod, treeCount);
distribution.AddRun(annealer, annealerRuntime, defaultParameters);
distribution.AddRun(deluge, delugeRuntime, defaultParameters);
distribution.AddRun(thresholdAcceptor, acceptorRuntime, defaultParameters);
distribution.AddRun(genetic, geneticRuntime, defaultParameters);
distribution.AddRun(enumerator, enumerationRuntime, defaultParameters);
distribution.AddRun(recordTravel, recordRuntime, defaultParameters);
distribution.AddRun(tabu, tabuRuntime, defaultParameters);
distribution.AddRun(random, randomRuntime, defaultParameters);
distribution.OnRunsComplete();
}
