| Bernoulli | This class simulates a "Bernoulli trial", which is like a coin toss |
| Binomial | This class simulates a "Binomial distribution" |
| Cauchy | This class simulates a "standard %Cauchy distribution" |
| Chromosome< T > | The super class for different type of chromosomes |
| Chromosome_Binary | Implement a binary-coded chromosome |
| Chromosome_Real | Implement a real-coded chromosome |
| Crossover< T > | The super class for crossover operators |
| Crossover_nPoint< T > | Implementation of n-point crossover (applicable for both binary/real-coded) |
| Crossover_Uniform< T > | Implementation of uniform crossover (applicable for both binary/real-coded) |
| DiffGeometric | This class simulates a "Differential %Geometric distribution" |
| DiscreteUniform | This class simulates a "uniform distribution" with integer numbers |
| Erlang | This class simulates an "%Erlang distribution" |
| FAckley | Implementation of the Ackley function. f(x) = -20 * exp(-0.2 * sqrt(sum{i = 1..n}(x(i) ^ 2) / n)) - exp(sum{i = 1..n}(cos(2 * PI * x(i))) / n) + 20 + exp(1) |
| FBump | Implementation of the Bump function. f(x) = frac{abs(sum(cos(x_i)^4) - 2prod(cos(x_i)^2))}{sqrt(sum{i=1}^n i*(x_i)^2)}; prod x_i > 0.75; sum x_i < 15*n/2 |
| FElliptic | Implementation of the Elliptic function |
| FFMS | Implementation of the Frequency Modulation of Sound function. f(x) = -20 * exp(-0.2 * sqrt(sum{i = 1..n}(x(i) ^ 2) / n)) - exp(sum{i = 1..n}(cos(2 * PI * x(i))) / n) + 20 + exp(1) |
| FGriewank | Implementation of the Griewank function. f(x) = sum{i = 1..n}(x(i) ^ 2) / 4000 - prod{i = 1..n}(cos(x(i) / sqrt(i))) + 1 |
| FGriewankRosenbrock | Implementation of the hybrid Griewank-Rosenbrock function |
| FRastrigin | Implementation of the Rastrigin function. f(x) = sum{i = 1..n}(x(i) ^ 2 - 10 * cos(2 * PI * x(i)) + 10) |
| FRosenbrock | Implementation of the Rosenbrock function. f(x) = sum{i = 1..(n - 1)}(100 * (x(i + 1) - x(i) ^ 2) ^ 2 + (x(i) - 1) ^ 2) |
| FScaffer | Implementation of the Scaffer function |
| FSchwefel102 | Implementation of the Schwefel function 1.02 |
| FSchwefel102Noisy | Implementation of the Schwefel function 1.02 with Gaussian noise |
| FSphere | Implementation of the Sphere function. f(x) = sum{i = 1..n}(x(i) ^ 2) |
| FStep | Implementation of the Step function. f(x) = 6n + \sum_{i=1}^n \floor{x_i} |
| FWeierstrass | Implementation of the Weierstrass function. f(x) = sum{i = 1..n}(sum{j = 0..k}(a ^ j * cos(2 * PI * b ^ j * (x(i) + 0.5)))) - n * sum{j = 0..k}(a ^ j * cos(PI * b ^ j)), a = 0.5, b = 3, k = 20 |
| GeneticAlgorithm< T > | This class implement standard Genetic Algorithm |
| Geometric | This class simulates a "%Geometric distribution" |
| GlobalSearch< T > | The super class for population-based search methods |
| HyperGeometric | This class simulates a "Hyper %Geometric distribution" |
| LocalSearch | The super class for local search methods |
| LocalSearch_DFP | Implement the Davidon-Fletcher-Powell Method |
| LocalSearch_DSCG | Implement the strategy of Davis, Swan and Campey, with Gram-Schmidt orthogonalization |
| LogNormal | This class simulates a "Log %Normal distribution" |
| MAMetaLamarckian< T > | Implemetation of Meta-Lamarckian MA |
| MemeticAlgorithm< T > | The super class for Memetic Algorithms |
| Mutation< T > | The super class for mutation operators |
| Mutation_BitFlip | Implementation of bit-flip mutation (applicable binary-coded chromosomes) |
| Mutation_Gaussian | Implementation of Gaussian mutation (applicable for real-coded chromosomes) |
| NegExponential | This class simulates a "negative exponential distribution" |
| Normal | This class simulates a "normal" distribution |
| ObjectiveFunction | The super class for objective functions |
| Poisson | This class simulates a "%Poisson distribution" |
| Population< T > | Population class |
| RandomVar< T > | Template class used as base for all random number generators of library "#Rng" |
| Recombination< T > | The super class for the recombination operators |
| Recombination_KeepBest< T > | Implementation of elitism recombination |
| Recombination_MuCommaLambda< T > | Implementation of mu comma lambda recombination |
| Recombination_MuPlusLambda< T > | Implementation of mu plus lambda recombination |
| RNG | This class defines a generator for uniformally distributed pseudo random numbers of the interval (0,1) |
| Rng | This class subsumes several often used random number generators |
| Scaling | The super class for the scaling operators |
| Scaling_Linear | Implementation of the linear scaling strategy |
| Selection< T > | The super class for the selection operators |
| Selection_RouletteWheel< T > | Implementation of the biased roulette wheel selection |
| Uniform | This class simulates a "uniform distribution" |
| Weibull | This class simulates a "%Weibull distribution" |
