public double FitnessValue(Individual secondInd, KnapsackList knapsackList)
{
bool strategy1 = this.strategy;
bool strategy2 = secondInd.strategy;
if (strategy1)
{
if (strategy2)
{
return(fitnessCooperativeCooperative(knapsackList));
}
else
{
return(fitnessCooperativeDefector(knapsackList));
}
}
else
{
if (strategy2)
{
return(fitnessDefectorCooperative(knapsackList));
}
else
{
return(fitnessDefectorDefector(knapsackList));
}
}
}
public double FitnessValue(KnapsackList knapsackList)
{
double sum = 0.0;
if (this.isFeasible)
{
for (int i = 0; i < this.chromosome.Count; i++)
{
sum += this.chromosome[i] ? knapsackList[0].GetValue(i) : 0.0;
}
return(sum / GA_GT.maxFitness);
}
else
{
double deltaV = GA_GT.cheatingDegree / 100.0;
for (int i = 0; i < this.chromosome.Count; i++)
{
sum += this.chromosome[i] ? knapsackList[0].GetValue(i) + deltaV : 0.0;
}
return((sum - NonFeasibleKnapsacks(knapsackList) * knapsackList[0].maxValue) / GA_GT.maxFitness);
}
}
public int NonFeasibleKnapsacks(KnapsackList knapsackList)
{
int counter = 0;
foreach (Knapsack k in knapsackList.knapsackList)
{
if (!this.chromosome.IsFeasible(k))
{
counter++;
}
}
return(counter);
}
static void Main(string[] args)
{
string path = @"..\..\samples\MK250.txt";
KnapsackList knapsackList = InputOutput.ReadInput(path);
knapsackList.Show();
init_static_GA_GT(knapsackList);
TestPopulation t = new TestPopulation();
GA_GT ga_gt = new GA_GT();
ga_gt.RunGA_GT().Show();
Console.WriteLine("End");
Console.ReadLine();
}
static void init_static_GA_GT(KnapsackList knapsackList)
{
GA_GT.gameModel = new PrisonersDilemma();
GA_GT.knapsackList = knapsackList;
GA_GT.weightGA = 0.8;
GA_GT.weightGT = 1.0 - GA_GT.weightGA;
GA_GT.cheatingDegree = 50;
GA_GT.cheaterRate = 0.1;
GA_GT.crossoverRate = 0.75;
GA_GT.numberOfEpochs = 1000;
GA_GT.chromosomeLength = InputOutput.objectsNumber;
GA_GT.populationSize = 40; // must be even number!!
GA_GT.mutationRate = 1.0 / GA_GT.chromosomeLength;
GA_GT.feasibleRate = 0.2;
}
static void init_static_GA_GT(KnapsackList knapsackList)
{
GA_GT.gameModel = new PrisonersDilemma();
GA_GT.knapsackList = knapsackList;
GA_GT.weightGA = 0.8;
GA_GT.weightGT = 1.0 - GA_GT.weightGA;
GA_GT.cheatingDegree = 50;
GA_GT.cheaterRate = 0.1;
GA_GT.crossoverRate = 0.75;
GA_GT.numberOfEpochs = 1000;
GA_GT.chromosomeLength = InputOutput.objectsNumber;
GA_GT.populationSize = 40; // must be even number!!
GA_GT.mutationRate = 1.0 / GA_GT.chromosomeLength;
GA_GT.feasibleRate = 0.2;
}
private double fitnessCooperativeDefector(KnapsackList knapsackList)
{
Knapsack knapsack = knapsackList[0];
double sum = 0.0;
for (int i = 0; i < this.chromosome.Count; i++)
{
sum += this.chromosome[i] ? knapsack.GetValue(i) : 0.0;
}
if (this.isFeasible)
{
return(GA_GT.weightGA * sum / GA_GT.maxFitness
+ GA_GT.weightGT * GA_GT.gameModel.cooperatorDefectorPayoff / GA_GT.maxPayoff);
}
else
{
return(GA_GT.weightGA * (sum - NonFeasibleKnapsacks(knapsackList) * knapsack.maxValue) / GA_GT.maxFitness
+ GA_GT.weightGT * GA_GT.gameModel.cooperatorDefectorPayoff / GA_GT.maxPayoff);
}
}
private double fitnessDefectorDefector(KnapsackList knapsackList)
{
Knapsack knapsack = knapsackList[0];
double deltaV = GA_GT.cheatingDegree / 100.0;
//double deltaW = GA_GT.cheatingDegree / 100.0;
double sum = 0.0;
for (int i = 0; i < this.chromosome.Count; i++)
{
sum += this.chromosome[i] ? knapsack.GetValue(i) + deltaV : 0.0;
}
if (this.isFeasible)
{
return(GA_GT.weightGA * sum / GA_GT.maxFitness
+ GA_GT.weightGT * GA_GT.gameModel.defectorDefectorPayoff / GA_GT.maxPayoff);
}
else
{
return(GA_GT.weightGA * (sum - NonFeasibleKnapsacks(knapsackList) * knapsack.maxValue) / GA_GT.maxFitness
+ GA_GT.weightGT * GA_GT.gameModel.defectorDefectorPayoff / GA_GT.maxPayoff);
}
}
public void Update(KnapsackList knapsackList)
{
isFeasible = chromosome.IsFeasible();
fitness = FitnessValue(knapsackList);
}
public double FitnessValue(Individual secondInd, KnapsackList knapsackList)
{
bool strategy1 = this.strategy;
bool strategy2 = secondInd.strategy;
if (strategy1)
{
if (strategy2)
{
return fitnessCooperativeCooperative(knapsackList);
}
else
{
return fitnessCooperativeDefector(knapsackList);
}
}
else
{
if (strategy2)
{
return fitnessDefectorCooperative(knapsackList);
}
else
{
return fitnessDefectorDefector(knapsackList);
}
}
}
private double fitnessDefectorDefector(KnapsackList knapsackList)
{
Knapsack knapsack = knapsackList[0];
double deltaV = GA_GT.cheatingDegree / 100.0;
//double deltaW = GA_GT.cheatingDegree / 100.0;
double sum = 0.0;
for (int i = 0; i < this.chromosome.Count; i++)
{
sum += this.chromosome[i] ? knapsack.GetValue(i) + deltaV : 0.0;
}
if (this.isFeasible)
{
return GA_GT.weightGA * sum / GA_GT.maxFitness
+ GA_GT.weightGT * GA_GT.gameModel.defectorDefectorPayoff / GA_GT.maxPayoff;
}
else
{
return GA_GT.weightGA * (sum - NonFeasibleKnapsacks(knapsackList) * knapsack.maxValue) / GA_GT.maxFitness
+ GA_GT.weightGT * GA_GT.gameModel.defectorDefectorPayoff / GA_GT.maxPayoff;
}
}
private double fitnessCooperativeDefector(KnapsackList knapsackList)
{
Knapsack knapsack = knapsackList[0];
double sum = 0.0;
for (int i = 0; i < this.chromosome.Count; i++)
{
sum += this.chromosome[i] ? knapsack.GetValue(i) : 0.0;
}
if (this.isFeasible)
{
return GA_GT.weightGA * sum / GA_GT.maxFitness
+ GA_GT.weightGT * GA_GT.gameModel.cooperatorDefectorPayoff / GA_GT.maxPayoff;
}
else
{
return GA_GT.weightGA * (sum - NonFeasibleKnapsacks(knapsackList) * knapsack.maxValue) / GA_GT.maxFitness
+ GA_GT.weightGT * GA_GT.gameModel.cooperatorDefectorPayoff / GA_GT.maxPayoff;
}
}
public void Update(KnapsackList knapsackList)
{
isFeasible = chromosome.IsFeasible();
fitness = FitnessValue(knapsackList);
}
public int NonFeasibleKnapsacks(KnapsackList knapsackList)
{
int counter = 0;
foreach (Knapsack k in knapsackList.knapsackList)
{
if (!this.chromosome.IsFeasible(k))
counter++;
}
return counter;
}
public double FitnessValue(KnapsackList knapsackList)
{
double sum = 0.0;
if (this.isFeasible)
{
for (int i = 0; i < this.chromosome.Count; i++)
{
sum += this.chromosome[i] ? knapsackList[0].GetValue(i) : 0.0;
}
return sum / GA_GT.maxFitness;
}
else
{
double deltaV = GA_GT.cheatingDegree / 100.0;
for (int i = 0; i < this.chromosome.Count; i++)
{
sum += this.chromosome[i] ? knapsackList[0].GetValue(i) + deltaV : 0.0;
}
return (sum - NonFeasibleKnapsacks(knapsackList) * knapsackList[0].maxValue) / GA_GT.maxFitness;
}
}
