public void TakeRandom_IEnumerable_Uniformity(int trialsQty, int toSelectQty, int elementsQty, int inRangeQty)
{
// Arrange
int expectedCount = trialsQty / (elementsQty / toSelectQty);
var timesChosen = new int[elementsQty];
var randomSelector = new RandomSelector();
// Act
for (var trial = 0; trial < trialsQty; trial++)
{
foreach (var selected in randomSelector.TakeRandom(Range(0, elementsQty), toSelectQty, timesChosen.Length))
{
timesChosen[selected]++;
}
}
var avg = timesChosen.Average();
var max = timesChosen.Max();
var min = timesChosen.Min();
var allowedDifference = expectedCount / elementsQty;
var countInRange = timesChosen.Count(i => i >= expectedCount - allowedDifference && i <= expectedCount + allowedDifference);
// Assert
AssertBetween(avg, expectedCount - 2, expectedCount + 2, "Average");
Assert.True(countInRange >= inRangeQty, string.Format("Not enough were in range: {0}", countInRange));
}
static void Main(string[] args)
{
List <string> stringList = new List <string>
{
"Bike", "Train", "Boat", "Feet"
};
List <Person> personList = new List <Person> {
new Person("Ted"),
new Person("Ira"),
new Person("Ada"),
new Person("Lea")
};
List <int> intList = new List <int> {
5, 10, 15, 20
};
RandomSelector <string> stringSelector = new RandomSelector <string>(stringList);
RandomSelector <Person> personSelector = new RandomSelector <Person>(personList);
RandomSelector <int> intSelector = new RandomSelector <int>(intList);
string choice = "";
while (choice != "q")
{
Console.WriteLine("Random string: " + stringSelector.Select().ToString());
Console.WriteLine("Random person: " + personSelector.Select().ToString());
Console.WriteLine("Random integer: " + intSelector.Select().ToString());
Console.Write("Again? Enter to continue, q to quit: ");
choice = Console.ReadLine();
}
}
public void ZeroSizeUtilityListSelectTest()
{
var uList = new List <Utility>();
var s = new RandomSelector();
Assert.That(s.Select(uList), Is.EqualTo(-1));
}
public Human(CivilizationManager civilManager, string name, HumanSex sex)
{
CivilManager = civilManager;
Name = name;
Sex = sex;
DieAge = RandomSelector.GetRandomDouble(CivilManager.GetSystem <SocialSystem>().Config.MaximumAge);
_stateMachine = new HumanStateMachine(this);
}
public void CloneTest()
{
var s = new RandomSelector();
Assert.IsNotNull(s);
var sc = s.Clone();
Assert.IsNotNull(sc);
}
public void When_running_then_complete_until_sucess_or_failure()
{
var s = new RandomSelector(new Helper().RunningTwiceThenSuccess(), new Helper().RunningTwiceThenSuccess(), new Helper().RunningTwiceThenSuccess());
s.Behave();
s.Behave();
s.Behave();
Assert.AreEqual(BehaviourReturnCode.Success, s.ReturnCode);
}
public void When_completed_then_new_task_starts()
{
var s = new RandomSelector(new Helper().RunningTwiceThenSuccess(), new Helper().RunningTwiceThenSuccess(), new Helper().RunningTwiceThenSuccess());
s.Behave();
s.Behave();
s.Behave();
s.Behave();
Assert.AreEqual(BehaviourReturnCode.Running, s.ReturnCode);
}
private ConcurrentQueue <Candidate> getRandomCandidates(List <Candidate> candList)
{
ConcurrentQueue <Candidate> participants = new ConcurrentQueue <Candidate>();
Parallel.For(0, TournamentSize, i => {
int index = RandomSelector.Next(0, candList.Count() - 1);
participants.Enqueue(candList[index]);
});
return(participants);
}
public static BComponent BuildComponent(XmlNode xmlDoc, BComponent parent, Behaviors behavior)
{
string name = xmlDoc.Name;
if (ActionBool.NAME == name)
{
return(ActionBool.Build(xmlDoc, parent, behavior));
}
else if (ActionProperty.NAME == name)
{
return(ActionProperty.Build(xmlDoc, parent, behavior));
}
else if (ActionVoid.NAME == name)
{
return(ActionVoid.Build(xmlDoc, parent, behavior));
}
else if (ActionEnumerator.NAME == name)
{
return(ActionEnumerator.Build(xmlDoc, parent, behavior));
}
else if (RandomSelector.NAME == name)
{
return(RandomSelector.Build(xmlDoc, parent, behavior));
}
else if (RootSelector.NAME == name)
{
return(RootSelector.Build(xmlDoc, parent, behavior));
}
else if (Selector.NAME == name)
{
return(Selector.Build(xmlDoc, parent, behavior));
}
else if (Sequence.NAME == name)
{
return(Sequence.Build(xmlDoc, parent, behavior));
}
else if (Inverter.NAME == name)
{
return(Inverter.Build(xmlDoc, parent, behavior));
}
else if (UntilTrue.NAME == name)
{
return(UntilTrue.Build(xmlDoc, parent, behavior));
}
else if (UntilFalse.NAME == name)
{
return(UntilFalse.Build(xmlDoc, parent, behavior));
}
else
{
Debug.LogErrorFormat("I did not find the item: {0}", name);
return(null);
}
}
private List <Candidate> getRandomCandidates(List <Candidate> candList)
{
List <Candidate> participants = new List <Candidate>();
for (int i = 0; i < TournamentSize; i++)
{
int index = RandomSelector.Next(0, candList.Count() - 1);
participants.Add(candList[index]);
}
return(participants);
}
public void AnItemIsReturned()
{
var itemList = new List <int>()
{
1, 2, 3
};
var selector = new RandomSelector <int>(new Random(), itemList);
var next = selector.PeekNext();
Assert.True(itemList.Contains(next));
}
public void SelectTest([Range(-1, 21, 1)] int selIdx)
{
var rn = new MockRandom();
rn.IntValue = selIdx;
var uList = SelectorTestsHelper.CreateRandomUtilityList(20);
var s = new RandomSelector(rn);
var aIdx = s.Select(uList);
var cIdx = selIdx.Clamp(0, 19);
Assert.That(aIdx, Is.EqualTo(cIdx));
}
internal static ICollectionSelector InitializeContentManager(TestContext testContext)
{
string sourceFolder = string.Empty;
string targetFolder = string.Empty;
bool reportsCreated = false;
List <string> scenarioList = null;
string runtimeResourcesSelector = null;
List <BadCombination> badCombinations = null;
List <ReportWeight> reportsWeight = null;
Logging.Log("Initialize Content for the test");
// Get runtime parameters
LoadContextProperty(testContext, SharedConstants.SourceReportFolderKey, ref sourceFolder);
LoadContextProperty(testContext, SharedConstants.TargetReportFolderKey, ref targetFolder);
LoadContextProperty(testContext, SharedConstants.ScenarioListKey, ref scenarioList);
LoadContextProperty(testContext, SharedConstants.RuntimeResourcesSelectorKey, ref runtimeResourcesSelector);
LoadContextProperty(testContext, SharedConstants.InitializedResourcesKey, ref reportsCreated);
LoadContextProperty <List <BadCombination> >(testContext, SharedConstants.BadCombinationsKey, ref badCombinations);
LoadContextProperty <List <ReportWeight> >(testContext, SharedConstants.ReportsWeightKey, ref reportsWeight);
ICollectionSelector itemSelector = null;
if (String.IsNullOrEmpty(runtimeResourcesSelector))
{
itemSelector = new RandomSelector();
}
else
{
if (runtimeResourcesSelector.Equals("random", StringComparison.InvariantCultureIgnoreCase))
{
itemSelector = new RandomSelector();
}
else
{
itemSelector = new SequentialSelector();
}
}
foreach (string scenario in scenarioList)
{
IContentManager contentManager = ContentManagerFactory.GetInstance(scenario);
contentManager.Initialize(scenario, scenario);
contentManager.ItemSelector = itemSelector;
contentManager.PopulateReportListFromServer();
contentManager.BadReportMethodCombinations = badCombinations;
contentManager.ReporstWeight = reportsWeight;
}
return(itemSelector);
}
public override bool InitializeSystem()
{
HumanSex sex = RandomSelector.GetRandomEnumValue <HumanSex>();
var family1Husband = HumanRecords.CreateRecord(null, RandomSelector.GetRandomName(HumanSex.Male), HumanSex.Male);
var family1Wife = HumanRecords.CreateRecord(null, RandomSelector.GetRandomName(HumanSex.Female), HumanSex.Female);
var family2Husband = HumanRecords.CreateRecord(null, RandomSelector.GetRandomName(HumanSex.Male), HumanSex.Male);
var family2Wife = HumanRecords.CreateRecord(null, RandomSelector.GetRandomName(HumanSex.Female), HumanSex.Female);
MarriageRecords.CreateRecord(family1Husband.Human as Man, family1Wife.Human as Woman);
MarriageRecords.CreateRecord(family2Husband.Human as Man, family2Wife.Human as Woman);
return(base.InitializeSystem());
}
private void fillBreedingPool(ConcurrentQueue <RouletteResult> results)
{
var TempBreeginPool = new ConcurrentQueue <Candidate>();
Parallel.For(0, selectionSize, i => {
double randomRouletteNumber;
randomRouletteNumber = RandomSelector.NextDouble();
Candidate temp = FindCandidate(results, randomRouletteNumber);
if (temp != null)
{
TempBreeginPool.Enqueue(temp);
}
});
BreedingPool = TempBreeginPool.ToList();
}
private static void randomMethodCalls()
{
Console.WriteLine("-- Random Method Calls --");
//add actions to the selector
var selector = RandomSelector
.Add(() => { Console.WriteLine("do first thing"); })
.Add(() => { Console.WriteLine("do other thing"); });
for (int i = 0; i < 5; i++)
{
selector.Choose(); //randomly picks an action to run
}
Console.WriteLine();
}
public override void Enter()
{
SocialSystem socialSystem = Controlled.CivilManager.GetSystem <SocialSystem>();
var suitableWomen = socialSystem.GetSuitableWomenForMarriage((Man)Controlled);
bool accepted = false;
Woman selectedWife = null;
while (!accepted && suitableWomen.Count > 0)
{
selectedWife = RandomSelector.SelectRandomSample(suitableWomen);
suitableWomen.Remove(selectedWife);
accepted = selectedWife.ResponseForMarriageProposal((Man)Controlled);
}
base.Enter();
}
private static void weightedRandomMethodCalls()
{
Console.WriteLine("-- Weighted Random Method Calls --");
//add actions to the selector (must add up to 1.0)
var selector = RandomSelector
.Add(0.7, () => { Console.WriteLine("0.7 - probably do this"); })
.Add(0.2, () => { Console.WriteLine("0.2 - maybe do this"); })
.Add(0.1, () => { Console.WriteLine("0.1 - small chance of this"); });
for (int i = 0; i < 5; i++)
{
selector.Choose(); //randomly picks an action to run
}
Console.WriteLine();
}
public void WhenCalledMultipleTimesTheSameItemIsReturned()
{
var itemList = new List <int>()
{
1, 2, 3
};
var random = new Mock <Random>();
random.SetupSequence(r => r.Next(It.IsAny <int>())).Returns(0).Returns(2);
var selector = new RandomSelector <int>(random.Object, itemList);
var first = selector.PeekNext();
var second = selector.PeekNext();
Assert.AreEqual(first, itemList[0]);
Assert.AreEqual(second, first);
}
public void test_1(){
_log.enterScope ();
RandomSelector rs = new RandomSelector (new BehaviorAction(component_1),
new BehaviorAction(component_2),
new BehaviorAction(component_3),
new BehaviorAction(component_4));
for (int i = 0; i < 100000; i++)
rs.Behave ();
_log.logMessage ("1:" + counts[0] +", 2:" + counts[1]+ ", 3:" + counts[2]+ ", 4:" + counts [3]);
Verify.VerifyTrue ("verify last component actioned", true, counts [3] > 0);
_log.exitScope ();
}
private static void weightedGeneric()
{
Console.WriteLine("-- Weighted Random Return Values --");
//add actions to the selector (must add up to 1.0)
var selector = RandomSelector <int>
.Add(0.7, 1)
.Add(0.2, 2)
.Add(0.1, 3);
for (int i = 0; i < 5; i++)
{
var val = selector.Choose(); //randomly picks an action to run
Console.WriteLine("chose " + val);
}
Console.WriteLine();
}
public void ProduceBaby()
{
SocialSystem socialSystem = CivilManager.GetSystem <SocialSystem>();
var marriageRecord = socialSystem.MarriageRecords.GetRecord(this);
var dieRecord = socialSystem.DieRecords.GetRecord(this);
if (marriageRecord == null || marriageRecord.RecordState == RecordState.Obselete ||
dieRecord != null)
{
return;
}
HumanSex childSex = RandomSelector.GetRandomEnumValue <HumanSex>();
string childName = RandomSelector.GetRandomName(childSex);
socialSystem.HumanRecords.CreateRecord(marriageRecord, childName, childSex);
}
public void WhenCalledMultipleTimesItemsAreRandom()
{
var itemList = new List <int>()
{
1, 2, 3
};
var random = new Mock <Random>();
random.SetupSequence(r => r.Next(It.IsAny <int>())).Returns(0).Returns(2).Returns(1);
var selector = new RandomSelector <int>(random.Object, itemList);
var first = selector.GetNext();
var second = selector.GetNext();
var third = selector.GetNext();
Assert.AreEqual(first, itemList[0]);
Assert.AreEqual(second, itemList[2]);
Assert.AreEqual(third, itemList[1]);
}
/// <summary>
/// Reproduction process
/// </summary>
private void Reproduce()
{
RandomSelector <Species> selector = new RandomSelector <Species>();
foreach (Species s in AllSpecies)
{
selector.Add(s, s.Score);
}
foreach (Client c in AllClients)
{
if (c.Species == null)
{
Species s = selector.Random();
c.Genome = s.Breed();
s.ForcePut(c);
}
}
}
private void fillBreedingPool(List <RouletteResult> results)
{
var TempBreedingPool = new List <Candidate>();
double randomRouletteNumber;
for (int i = 0; i < selectionSize; i++)
{
randomRouletteNumber = RandomSelector.NextDouble();
Candidate temp = FindCandidate(results, randomRouletteNumber);
if (temp != null)
{
TempBreedingPool.Add(temp);
}
else
{
i--;
}
}
BreedingPool = TempBreedingPool.ToList();
}
static void Main(string[] args)
{
IEnumerable <AMenu> menus = new List <AMenu>()
{
new 국밥(),
new 돈까스(),
new 라면(),
new 스파게티()
};
ISelectable selectable = new HighPriceSelector();
Console.WriteLine(new MenuSelector(menus, selectable).GetMenu().Explain());
selectable = new LowPriceSelector();
Console.WriteLine(new MenuSelector(menus, selectable).GetMenu().Explain());
selectable = new RandomSelector();
Console.WriteLine(new MenuSelector(menus, selectable).GetMenu().Explain());
}
public void test_1()
{
_log.enterScope();
RandomSelector rs = new RandomSelector(new BehaviorAction(component_1),
new BehaviorAction(component_2),
new BehaviorAction(component_3),
new BehaviorAction(component_4));
for (int i = 0; i < 100000; i++)
{
rs.Behave();
}
_log.logMessage("1:" + counts[0] + ", 2:" + counts[1] + ", 3:" + counts[2] + ", 4:" + counts [3]);
Verify.VerifyTrue("verify last component actioned", true, counts [3] > 0);
_log.exitScope();
}
public void chooseOption()
{
StatusWindowText.text = "The Enemy is Contemplating...";
int[] rootWeights = { 40, 40, 20 };
List <Node> level2 = new List <Node>();
List <Node> level3_1 = new List <Node>();
List <Node> level3_2 = new List <Node>();
level2.Add(new Call(basicAttack));
level3_1.Add(new Call(debuffDefense));
level3_2.Add(new Call(shoot));
level2.Add(new If(playerBuffedDefense, level3_1));
level2.Add(new IfInt(enoughSP, 10, level3_2));
RandomSelector Root = new RandomSelector(3, level2, rootWeights);
/*Current implementation: First check if player buffed defense. If yes, debuff defense defense. If no, attack
*/
//if (PlayerStats.GetComponent<UnitStats>().defense > 10)
//{
// CombatStateMachine.GetComponent<CombatStateM>().movePower = 0;
// PlayerStats.GetComponent<UnitStats>().defense = PlayerStats.GetComponent<UnitStats>().defense / 2;
// StatusWindowText.text = "The enemy screeched, lowering your defense";
//}
//else
//{
// CombatStateMachine.GetComponent<CombatStateM>().movePower = 5;
// StatusWindowText.text = "The enemy strikes";
//}
if (Root.Evaluate() == Node.NodeStates.SUCCESS)
{
CombatStateMachine.GetComponent <CombatStateM>().currState = CombatStateM.CombatState.EnemyCombat;
}
}
public void RandomSelector_Normal_Test()
{
int length = 10;
int attempts = 1000;
//на большом числе проходов мы "убеждаемся" что получены все числа от 0...length-1
//Тест не-дерерминирован, и на самом деле интеграционный
Dictionary <int, object> randomResults = new Dictionary <int, object>();
var selector = new RandomSelector();
for (int i = 0; i < attempts; i++)
{
int result = selector.GetRandomIndex(length);
randomResults[result] = null;
}
//теперь проверка что все варианты "вошли" в набор
for (int i = 0; i < length; i++)
{
Assert.IsTrue(randomResults.ContainsKey(i), $"Очікувалося що в результаті буде {i}");
}
}
/// <summary>
/// Solves the problem using a GA.
/// </summary>
/// <param name="problem"></param>
/// <returns></returns>
protected override IRoute DoSolve(OsmSharp.Tools.Math.TSP.Problems.IProblem problem)
{
//int population_size = 10;
//if (problem.Size < 100)
//{
// population_size = System.Math.Max(problem.Size * 3, 10);
// if (problem.Size < 10)
// {
// population_size = 1;
// }
//}
//if (problem.Size < 1000)
//{
// population_size = problem.Size / 4;
//}
// create the settings.
SolverSettings settings = new SolverSettings(
_stagnation_count,
_population,
1000000000,
_eltism,
_cross,
_mutation);
//List<IMutationOperation<List<int>, GeneticProblem, Fitness>> mutators = new List<IMutationOperation<int,GeneticProblem,Fitness>>();
////mutators.Add(new DefaultMutationOperation());
////mutators.Add(new BestPlacementMutationOperation());
//mutators.Add(new BestDetailedPlacementMutationOperation());
//List<double> probabilities = new List<double>();
//probabilities.Add(1);
////probabilities.Add(0.5);
////probabilities.Add(0.3);
//CombinedMutation<List<int>, GeneticProblem, Fitness> mutation = new CombinedMutation<int,GeneticProblem,Fitness>(
// StaticRandomGenerator.Get(),
// mutators,
// probabilities);
////SequentialContructiveCrossoverOperator cross_over = new SequentialContructiveCrossoverOperator();
//BestDetailedPlacementCrossOverOperation cross_over = new BestDetailedPlacementCrossOverOperation();
////BestPlacementCrossOverOperation cross_over = new BestPlacementCrossOverOperation();
////EdgeRecombinationCrossOverOperation cross_over = new EdgeRecombinationCrossOverOperation();
//BestPlacementGenerationOperation generation = new BestPlacementGenerationOperation();
////RandomGenerationOperation generation = new RandomGenerationOperation();
ISelector<List<int>, GeneticProblem, Fitness> selector = new RandomSelector<List<int>, GeneticProblem, Fitness>();
//ISelector<List<int>, GeneticProblem, Fitness> selector = new TournamentBasedSelector<List<int>, GeneticProblem, Fitness>(75, 0.01);
solver =
new Solver<List<int>, GeneticProblem, Fitness>(
new GeneticProblem(problem),
settings,
selector,
_mutation_operation,
_cross_over_operation,
_generation_operation,
new FitnessCalculator(),
true, false);
solver.NewFittest += new Solver<List<int>, GeneticProblem, Fitness>.NewFittestDelegate(solver_NewFittest);
solver.NewGeneration += new Solver<List<int>, GeneticProblem, Fitness>.NewGenerationDelegate(solver_NewGeneration);
List<int> result = new List<int>(solver.Start(null).Genomes);
result.Insert(0, 0);
return new SimpleAsymmetricRoute(result, true);
}
public void DrawInspector(RandomSelector node)
{
EditorGUILayout.LabelField(new GUIContent("Random Selector"), TitleStyle);
EditorGUILayout.Space ();
if (node.ChildCount > 0) {
float chance = 100f / node.ChildCount;
EditorGUILayout.LabelField(new GUIContent("Each child has a " + chance.ToString ("F1") + "% chance of being selected."), SubtitleStyle);
}
string message = "The Random Selector sends the tick signal to one of its children, selected at random, and returns the state returned by that child.";
EditorGUILayout.HelpBox(message, MessageType.Info);
EditorGUILayout.HelpBox("Not yet implemented!", MessageType.Error);
}
/// <summary>
/// 消えた部屋につながっていた袋小路の処理
/// </summary>
/// <param name="room"></param>
void ProcessDeadEnd(DungeonRoom room)
{
var deadends = new List<DungeonPath>();
UpdateAccessibility();
foreach (var portal in room.Portals)
{
if (portal.ConnectedPaths.Count == 0)
continue;
var path = portal.ConnectedPaths[0];
if (path.Accessible)
{
// 袋小路をリストアップ
deadends.Add(path);
}
else
{
// 孤立している通路は消す
RemovePath(path);
}
}
var selector = new RandomSelector<DeadEndDisposal>(Rand);
selector.Add(40, DeadEndDisposal.CONNECT);
selector.Add(55, DeadEndDisposal.REMOVE);
selector.Add(5, DeadEndDisposal.LEAVE);
while (deadends.Count > 0)
{
var disposal = selector.Get();
if (disposal == DeadEndDisposal.CONNECT && deadends.Count >= 2)
{
var another = Rand.Next(1, deadends.Count);
var portals = new DungeonPortal[2]{
deadends[0].GetTerminalPortal(),
deadends[another].GetTerminalPortal()
};
var path = GeneratePath(
portals[0],
portals[1],
IsHorizontalPortals(portals[0], portals[1])
);
if (path != null)
{
AddPath(path);
deadends.RemoveAt(another);
}
deadends.RemoveAt(0);
}
else if (disposal == DeadEndDisposal.REMOVE)
{
RemovePath(deadends[0]);
deadends.RemoveAt(0);
}
else if (disposal == DeadEndDisposal.LEAVE)
{
deadends.RemoveAt(0);
}
}
}
private static BT CreateStreetBT(DataModel d)
{
Sequence wander = new Sequence {
new While(
new Sequence {
new RandomSelector
{
new Sequence //wandersteer
{
new SetMovementSpeed(d, false),
new Wander(d),
new RandomWait(0.5f, 1.0f)
},
new Sequence //move to poi
{
new SetMovementSpeed(d, false),
new SetTarget(d, PointType.Interest, PointList.GetRandomPoint),
new Seek(d, x => x.Target),
new RandomWait(0.5f, 1.0f)
}
}
},
new Sequence
{
}
)
};
Sequence attack = new Sequence
{
new ReloadWeapon(d),
new UseItem(d),
new CausePanic(d),
new Wait(1f),
new Succeeder(new While
(
new CanSeeTarget(d, true),
new Seek(d, x => x.Target)
)),
};
Selector equipWeapon = new Selector //Equiping a weapon
{
new IsWeaponEquipped(d), //If NPC has a weapon, do nothing else equip
new Sequence
{
new EquipRandomWeapon(d),
new Wait(3f)
}
};
While runIntoRange = new While( //movetotarget
new Sequence
{
new IsWithinWeaponsRange(d, true),
// new CanSeeTarget(d, true)
},
new Seek(d, x => x.Target) //If the target is not visable, seek the target.
);
RandomSelector selectTarget = new RandomSelector
{
new SetTarget(d),
new SetTarget(d, true)
};
Sequence canAttack = new Sequence //use conditions
{
new IsWithinWeaponsRange(d),
new IsTargetAlive(d),
new TurnToFaceTarget(d, 180),
};
Sequence flee = new Sequence //run away
{
new SetMovementSpeed(d, true),
new SetTarget(d, PointType.Despawn, PointList.GetSafestPoint),
new Succeeder(new Seek(d, x => x.Target)),
new Despawn(d)
};
Sequence rootSelector = new Sequence
{
new While(
new IsPanicking(d), //panic
flee
),
new Sequence {
new While( //Continues as long as everthing returns true
new Sequence //Step 1. If NPC is hostile continue
{
new IsHostile(d),
new CanAttack(d)
},
new Sequence //Step 2, starting attack
{
new SetMovementSpeed(d, true), //Allows npc to run
new While(new IsTargetAlive(d, true), selectTarget),
equipWeapon,
runIntoRange,
new While(
canAttack,
new Repeater(attack, true)
),
}
)
},
wander,
};
return(new BT(rootSelector));
}
/// <summary>
/// Solves the problem using a GA.
/// </summary>
/// <param name="problem"></param>
/// <returns></returns>
protected override IRoute DoSolve(OsmSharp.Math.TSP.Problems.IProblem problem)
{
//int population_size = 10;
//if (problem.Size < 100)
//{
// population_size = System.Math.Max(problem.Size * 3, 10);
// if (problem.Size < 10)
// {
// population_size = 1;
// }
//}
//if (problem.Size < 1000)
//{
// population_size = problem.Size / 4;
//}
// create the settings.
SolverSettings settings = new SolverSettings(
_stagnation_count,
_population,
1000000000,
_eltism,
_cross,
_mutation);
//List<IMutationOperation<List<int>, GeneticProblem, Fitness>> mutators = new List<IMutationOperation<int,GeneticProblem,Fitness>>();
////mutators.Add(new DefaultMutationOperation());
////mutators.Add(new BestPlacementMutationOperation());
//mutators.Add(new BestDetailedPlacementMutationOperation());
//List<double> probabilities = new List<double>();
//probabilities.Add(1);
////probabilities.Add(0.5);
////probabilities.Add(0.3);
//CombinedMutation<List<int>, GeneticProblem, Fitness> mutation = new CombinedMutation<int,GeneticProblem,Fitness>(
// StaticRandomGenerator.Get(),
// mutators,
// probabilities);
////SequentialContructiveCrossoverOperator cross_over = new SequentialContructiveCrossoverOperator();
//BestDetailedPlacementCrossOverOperation cross_over = new BestDetailedPlacementCrossOverOperation();
////BestPlacementCrossOverOperation cross_over = new BestPlacementCrossOverOperation();
////EdgeRecombinationCrossOverOperation cross_over = new EdgeRecombinationCrossOverOperation();
//BestPlacementGenerationOperation generation = new BestPlacementGenerationOperation();
////RandomGenerationOperation generation = new RandomGenerationOperation();
ISelector <List <int>, GeneticProblem, Fitness> selector = new RandomSelector <List <int>, GeneticProblem, Fitness>();
//ISelector<List<int>, GeneticProblem, Fitness> selector = new TournamentBasedSelector<List<int>, GeneticProblem, Fitness>(75, 0.01);
solver =
new Solver <List <int>, GeneticProblem, Fitness>(
new GeneticProblem(problem),
settings,
selector,
_mutation_operation,
_cross_over_operation,
_generation_operation,
new FitnessCalculator(),
true, false);
solver.NewFittest += new Solver <List <int>, GeneticProblem, Fitness> .NewFittestDelegate(solver_NewFittest);
solver.NewGeneration += new Solver <List <int>, GeneticProblem, Fitness> .NewGenerationDelegate(solver_NewGeneration);
List <int> result = new List <int>(solver.Start(null).Genomes);
result.Insert(0, 0);
return(new SimpleAsymmetricRoute(result, true));
}
