public Position calculateAlpha(List<Krill> herd, Krill krill, HerdParameters parameters)
{
Position localAlpha = calculateAlphaLocal(herd, krill, parameters);
Position targetAlpha = calculateAlphaTarget(parameters,krill);
return localAlpha + targetAlpha;
}
public Position calculateAlpha(List <Krill> herd, Krill krill, HerdParameters parameters)
{
Position localAlpha = calculateAlphaLocal(herd, krill, parameters);
Position targetAlpha = calculateAlphaTarget(parameters, krill);
return(localAlpha + targetAlpha);
}
public Position calculateBeta(Krill krill, Food food, HerdParameters parameters)
{
Position betaFood = calculateBetaFood(food,krill);
Position betaBest = calculateBetaBest(krill,parameters);
//Debug.Log("Food " + betaFood + " best " + betaBest);
return betaFood + betaBest;
}
private void mutateKrill(Krill krill, List<Krill> herd, HerdParameters parameters)
{
int range = herd.Count / 2;
Krill first = herd[Random.Range(0,range)];
int secondIndex = Random.Range(range,herd.Count);
Krill second = herd[secondIndex];
// krill.mutate(first,second,parameters.getBestFitnessKrill());
}
private Position calculateBetaBest(Krill krill, HerdParameters parameters)
{
Position bestRelatedPosition = tendencyCalculator.calculateRelatedPosition(krill.getBestPosition(),krill.getPosition());
float bestFitness = tendencyCalculator.calculateRelatedFitness(krill.getFitnessValue(),krill.getBestPositionFitness(),parameters);
//Debug.Log("best fitness " + bestFitness);
bestRelatedPosition = bestRelatedPosition * bestFitness;
return bestRelatedPosition;
}
public Position calculateBeta(Krill krill, Food food, HerdParameters parameters)
{
Position betaFood = calculateBetaFood(food, krill);
Position betaBest = calculateBetaBest(krill, parameters);
//Debug.Log("Food " + betaFood + " best " + betaBest);
return(betaFood + betaBest);
}
private void mutateKrill(Krill krill, List <Krill> herd, HerdParameters parameters)
{
int range = herd.Count / 2;
Krill first = herd[Random.Range(0, range)];
int secondIndex = Random.Range(range, herd.Count);
Krill second = herd[secondIndex];
// krill.mutate(first,second,parameters.getBestFitnessKrill());
}
private Position calculateBetaBest(Krill krill, HerdParameters parameters)
{
Position bestRelatedPosition = tendencyCalculator.calculateRelatedPosition(krill.getBestPosition(), krill.getPosition());
float bestFitness = tendencyCalculator.calculateRelatedFitness(krill.getFitnessValue(), krill.getBestPositionFitness(), parameters);
//Debug.Log("best fitness " + bestFitness);
bestRelatedPosition = bestRelatedPosition * bestFitness;
return(bestRelatedPosition);
}
public void calculateForagingMotion(List<Krill> herd, HerdParameters parameters, Food food)
{
foreach(Krill krill in herd){
Position oldForaging = krill.getForagingMotion() * parameters.inertiaForagingWeight;
Position betaPosition = betaCalculator.calculateBeta(krill,food,parameters);
betaPosition = betaPosition * parameters.Vf;
krill.setForagingMotion(betaPosition + oldForaging);
}
}
public void calculateDiffusionMotion(List<Krill> herd,HerdParameters parameters)
{
foreach(Krill krill in herd){
Position randomizedPosition = randomizePosition();
randomizedPosition = randomizedPosition * parameters.randomizeDMAX();
randomizedPosition = randomizedPosition * calculateIterationRatio(parameters);
krill.setDiffusionMotion(randomizedPosition);
}
}
public void crossoverHerd(List<Krill> herd, HerdParameters parameters)
{
foreach (Krill krill in herd) {
float Cr = 0.2f * tendencyCalculator.calculateRelatedFitness(krill.getFitnessValue(), parameters.getBestFitnessValue(), parameters);
float ran = Random.Range(0.0f,1.0f);
if (ran < Cr) {
crossKrill(krill, herd);
}
}
}
public void calculateMotion(List<Krill> herd, HerdParameters algorithmParameters)
{
foreach(Krill krill in herd){
Position oldMotion = krill.getMotionInduced()*algorithmParameters.inertiaWeight;
Position alphaPosition = getAlphaPosition(herd,krill,algorithmParameters);
Position newMotionPosition = alphaPosition + oldMotion;
krill.setMotionInduced(newMotionPosition);
}
}
public void calculateForagingMotion(List <Krill> herd, HerdParameters parameters, Food food)
{
foreach (Krill krill in herd)
{
Position oldForaging = krill.getForagingMotion() * parameters.inertiaForagingWeight;
Position betaPosition = betaCalculator.calculateBeta(krill, food, parameters);
betaPosition = betaPosition * parameters.Vf;
krill.setForagingMotion(betaPosition + oldForaging);
}
}
private Position calculateAlphaTarget(HerdParameters parameters, Krill krill)
{
Position relatedPosition = tendencyCalculator.calculateRelatedPosition(parameters.getBestFitnessPosition(), krill.getPosition());
float relatedFitness = tendencyCalculator.calculateRelatedFitness(krill.getFitnessValue(), parameters.getBestFitnessValue(), parameters);
relatedPosition = relatedPosition * relatedFitness;
relatedPosition = relatedPosition * calculateCoefficient(parameters);
return(relatedPosition);
}
private Position calculateAlphaTarget(HerdParameters parameters, Krill krill)
{
Position relatedPosition = tendencyCalculator.calculateRelatedPosition(parameters.getBestFitnessPosition(), krill.getPosition());
float relatedFitness = tendencyCalculator.calculateRelatedFitness(krill.getFitnessValue(),parameters.getBestFitnessValue(), parameters);
relatedPosition = relatedPosition * relatedFitness;
relatedPosition = relatedPosition * calculateCoefficient(parameters);
return relatedPosition;
}
public void calculateDiffusionMotion(List <Krill> herd, HerdParameters parameters)
{
foreach (Krill krill in herd)
{
Position randomizedPosition = randomizePosition();
randomizedPosition = randomizedPosition * parameters.randomizeDMAX();
randomizedPosition = randomizedPosition * calculateIterationRatio(parameters);
krill.setDiffusionMotion(randomizedPosition);
}
}
public void calculateMotion(List <Krill> herd, HerdParameters algorithmParameters)
{
foreach (Krill krill in herd)
{
Position oldMotion = krill.getMotionInduced() * algorithmParameters.inertiaWeight;
Position alphaPosition = getAlphaPosition(herd, krill, algorithmParameters);
Position newMotionPosition = alphaPosition + oldMotion;
krill.setMotionInduced(newMotionPosition);
}
}
public void mutateHerd(List<Krill> herd, HerdParameters parameters)
{
foreach (Krill krill in herd) {
float Mu = 0.05f / tendencyCalculator.calculateRelatedFitness(krill.getFitnessValue(), parameters.getBestFitnessValue(), parameters);
float ran = Random.Range(0.0f,1.0f);
if (ran < Mu) {
mutateKrill(krill, herd, parameters);
}
}
}
public void crossoverHerd(List <Krill> herd, HerdParameters parameters)
{
foreach (Krill krill in herd)
{
float Cr = 0.2f * tendencyCalculator.calculateRelatedFitness(krill.getFitnessValue(), parameters.getBestFitnessValue(), parameters);
float ran = Random.Range(0.0f, 1.0f);
if (ran < Cr)
{
crossKrill(krill, herd);
}
}
}
public CircleKrillSetter(HerdParameters parameters)
{
this.parameters = parameters;
speeds = new float[5,2]{ {100.0f,120.0f} , {120.0f,160.0f}, {170.0f,200.0f},{120.0f,160.0f},{100.0f,120.0f}};
//speeds = new float[3,2]{{120.0f,160.0f}, {170.0f,200.0f},{120.0f,160.0f}};
//speeds = new float[7,2]{ {80.0f,100.0f} , {100.0f,120.0f}, {120.0f,160.0f},{160.0f,200.0f},{120.0f,160.0f},{100.0f,120.0f},{80.0f,100.0f}};
partSize = (parameters.herdSize - parameters.herdSize%2)/2;
angle = triangleAngleSize/(parameters.herdSize - parameters.herdSize%2);
triangleArm = 2.0f * height * Mathf.Sqrt(3.0f)/3.0f;
delta = (triangleArm - height)/partSize;
herdSize = parameters.herdSize;
}
private Position calculateAlphaLocal(List<Krill> neighbours, Krill krill, HerdParameters parameters)
{
Position alphaLocal = new Position();
foreach (Krill neighbour in neighbours) {
Position relatedPosition = tendencyCalculator.calculateRelatedPosition(neighbour.getPosition(), krill.getPosition());
float relatedFitness = tendencyCalculator.calculateRelatedFitness(krill.getFitnessValue(),neighbour.getFitnessValue(), parameters);
relatedPosition = relatedPosition * relatedFitness;
alphaLocal = alphaLocal + relatedPosition;
}
return alphaLocal;
}
public void mutateHerd(List <Krill> herd, HerdParameters parameters)
{
foreach (Krill krill in herd)
{
float Mu = 0.05f / tendencyCalculator.calculateRelatedFitness(krill.getFitnessValue(), parameters.getBestFitnessValue(), parameters);
float ran = Random.Range(0.0f, 1.0f);
if (ran < Mu)
{
mutateKrill(krill, herd, parameters);
}
}
}
public CircleKrillSetter(HerdParameters parameters)
{
this.parameters = parameters;
speeds = new float[5, 2] {
{ 100.0f, 120.0f }, { 120.0f, 160.0f }, { 170.0f, 200.0f }, { 120.0f, 160.0f }, { 100.0f, 120.0f }
};
//speeds = new float[3,2]{{120.0f,160.0f}, {170.0f,200.0f},{120.0f,160.0f}};
//speeds = new float[7,2]{ {80.0f,100.0f} , {100.0f,120.0f}, {120.0f,160.0f},{160.0f,200.0f},{120.0f,160.0f},{100.0f,120.0f},{80.0f,100.0f}};
partSize = (parameters.herdSize - parameters.herdSize % 2) / 2;
angle = triangleAngleSize / (parameters.herdSize - parameters.herdSize % 2);
triangleArm = 2.0f * height * Mathf.Sqrt(3.0f) / 3.0f;
delta = (triangleArm - height) / partSize;
herdSize = parameters.herdSize;
}
private Position calculateAlphaLocal(List <Krill> neighbours, Krill krill, HerdParameters parameters)
{
Position alphaLocal = new Position();
foreach (Krill neighbour in neighbours)
{
Position relatedPosition = tendencyCalculator.calculateRelatedPosition(neighbour.getPosition(), krill.getPosition());
float relatedFitness = tendencyCalculator.calculateRelatedFitness(krill.getFitnessValue(), neighbour.getFitnessValue(), parameters);
relatedPosition = relatedPosition * relatedFitness;
alphaLocal = alphaLocal + relatedPosition;
}
return(alphaLocal);
}
public Food(HerdParameters herdParameters, Transform visualFoodTransform)
{
sectorManager = GameObject.FindGameObjectWithTag("Sector").GetComponent<SectorsManager>();
pointsCointainer = sectorManager.getContainerClone();
List<Vector3> initialTrace = pointsCointainer.getAllMapPoints();
positions = new Position[initialTrace.Count];
visualFoodPosition = visualFoodTransform;
this.herdParameters = herdParameters;
for(int i = 0; i < initialTrace.Count; i++){
positions[i] = new Position(initialTrace[i]);
}
initCenterPositions();
}
public Food(HerdParameters herdParameters, Transform visualFoodTransform)
{
sectorManager = GameObject.FindGameObjectWithTag("Sector").GetComponent <SectorsManager>();
pointsCointainer = sectorManager.getContainerClone();
List <Vector3> initialTrace = pointsCointainer.getAllMapPoints();
positions = new Position[initialTrace.Count];
visualFoodPosition = visualFoodTransform;
this.herdParameters = herdParameters;
for (int i = 0; i < initialTrace.Count; i++)
{
positions[i] = new Position(initialTrace[i]);
}
initCenterPositions();
}
public float calculateRelatedFitness(float krillFitness, float neighbourFitness, HerdParameters parameters)
{
return((krillFitness - neighbourFitness) / parameters.getRelatedFitnessValue());
}
public float calculateRelatedFitness(float krillFitness,float neighbourFitness, HerdParameters parameters)
{
return (krillFitness - neighbourFitness) / parameters.getRelatedFitnessValue();
}
private float calculateIterationRatio(HerdParameters parameters)
{
return 1.0f - parameters.getIterationRatio();
}
private void init()
{
algorithmParameters = new HerdParameters();
herd = krillSetter.initHerd(carTransform, krillViz);
}
private float calculateIterationRatio(HerdParameters parameters)
{
return(1.0f - parameters.getIterationRatio());
}
private float calculateCoefficient(HerdParameters parameters)
{
return(2.0f * (Random.Range(0.0f, 1.0f) + parameters.getIterationRatio()));
}
private float calculateCoefficient(HerdParameters parameters)
{
return 2.0f * (Random.Range(0.0f,1.0f) + parameters.getIterationRatio());
}
private Position getAlphaPosition(List <Krill> herd, Krill krill, HerdParameters parameters)
{
Position alphaPosition = alphaCalculator.calculateAlpha(herd, krill, parameters);
return(alphaPosition * parameters.N_MAX);
}
public void updatePosition(Vector3 carPosition, HerdParameters parameters)
{
position = position + (motionInduced + diffusionMotion) * parameters.delta_t;
visualizeKrill(carPosition);
}
private Position getAlphaPosition(List<Krill> herd,Krill krill, HerdParameters parameters)
{
Position alphaPosition = alphaCalculator.calculateAlpha(herd,krill,parameters);
return alphaPosition * parameters.N_MAX;
}
private void init()
{
algorithmParameters = new HerdParameters();
herd = krillSetter.initHerd(carTransform,krillViz);
}
public void updatePosition(Vector3 carPosition, HerdParameters parameters)
{
position = position + (motionInduced + diffusionMotion) * parameters.delta_t;
visualizeKrill(carPosition);
}
