public void TestPerformOptimizationReturnsLocalExtrema()
{
TestIntegerEvaluableState initial = new TestIntegerEvaluableState(2);
TestIntegerEvaluableState result;
generator = new TestIntegerLocalMaximaSuccessorGenerator();
picker = new ClimberSuccessorPicker <TestIntegerEvaluableState, int>(generator, comparer);
algorithm = new LocalClimberAlgorithm <TestIntegerEvaluableState, int>(comparer, picker);
climber = new GeneralHillClimber <TestIntegerEvaluableState>(algorithm);
Task <TestIntegerEvaluableState> optimizeTask = Task.Run(() => climber.PerformOptimization(initial));
bool complete = false;
Stopwatch timer = new Stopwatch();
timer.Start();
while (!complete && timer.ElapsedMilliseconds < 5000)
{
complete = optimizeTask.IsCompleted;
}
timer.Stop();
Assert.IsTrue(complete, "Optimization did not stop at local extraema");
result = optimizeTask.Result;
Assert.AreEqual(50, result.Value);
}
public void Setup()
{
comparer = new MaximizingComparer <int>();
generator = new TestLinearIntegerSuccessorGenerator();
picker = new ClimberSuccessorPicker <TestIntegerEvaluableState, int>(generator, comparer);
algorithm = new LocalClimberAlgorithm <TestIntegerEvaluableState, int>(comparer, picker);
climber = new GeneralHillClimber <TestIntegerEvaluableState>(algorithm);
}
public void TestRandomRestartHillClimberSameRestartPointEachTime()
{
comparer = new MaximizingComparer <int>();
generator = new TestLinearIntegerSuccessorGenerator();
picker = new ClimberSuccessorPicker <TestIntegerEvaluableState, int>(generator, comparer);
algorithm = new LocalClimberAlgorithm <TestIntegerEvaluableState, int>(comparer, picker);
randomizer = new TestIntegerEvaluableStateNonRandomizer();
climber = new RandomRestartHillClimber <TestIntegerEvaluableState, int>(randomizer, algorithm, 5);
RunTest(climber, 2, 100);
}
public void TestRandomRestartHillClimberIncrementingRestartPoint()
{
comparer = new MaximizingComparer <int>();
generator = new TestExponentialIntegerSuccessorGenerator();
picker = new ClimberSuccessorPicker <TestIntegerEvaluableState, int>(generator, comparer);
algorithm = new LocalClimberAlgorithm <TestIntegerEvaluableState, int>(comparer, picker);
randomizer = new TestIntegerRandomizerSimulator();
climber = new RandomRestartHillClimber <TestIntegerEvaluableState, int>(randomizer, algorithm, 5);
RunTest(climber, 1, 64);
}
/// <summary>
/// Returns the configured <see cref="IClimberAlgorithm{TState, TEvaluation}"/> if it is available or creates a default one with the given configuration.
/// </summary>
/// <returns>The <see cref="IClimberAlgorithm{TState, TEvaluation}"/> for this configuration</returns>
private IClimberAlgorithm <TState, TEvaluation> ResolveAlgorithm(IComparer <TState> comparer, Func <TState, IEnumerable <TState> > successorGenerationFunction)
{
IClimberAlgorithm <TState, TEvaluation> algorithm;
// create a climber algorithm if one is not already configured
if (ClimberAlgorithm == null)
{
ClimberSuccessorSelector <TState, TEvaluation> successorSelector = new ClimberSuccessorSelector <TState, TEvaluation>(comparer, successorGenerationFunction);
algorithm = new LocalClimberAlgorithm <TState, TEvaluation>(successorSelector);
}
else
{
algorithm = ClimberAlgorithm;
}
return(algorithm);
}
public void TestPerformOptimizationReturnsLocalExtrema()
{
TestIntegerEvaluableState initial = new TestIntegerEvaluableState(2);
TestIntegerEvaluableState result;
generator = new TestIntegerLocalMaximaSuccessorGenerator();
picker = new ClimberSuccessorSelector <TestIntegerEvaluableState, int>(generator, comparer);
algorithm = new LocalClimberAlgorithm <TestIntegerEvaluableState, int>(picker);
climber = new ClimberConfiguration <TestIntegerEvaluableState, int>()
.ComparesUsing(comparer)
.GeneratesSuccessorsWith(generator)
.Build();
result = climber.Optimize(initial);
Assert.AreEqual(50, result.Value);
}
