| Class | Description |
|---|---|
| Gene | Represents a template for defining a possible problem solution (gene). By performing GA operations on Genes Genetic Algorithms can effectivly search problem space for the solution. |
| GeneCollection | Represent a collection of Genes. |
| GenerationalGA | Implementation of Generational Genetic Algorithms. |
| GeneticAlgorithm | Provides a pre-wired skeleton for implementation of GeneticAlgorithm. |
| GeneticAlgorithm.NewGenerationEventArgs | Provides data for NewGeneration event. |
| GeneticAlgorithm.SolutionFoundEventArgs | Provides data for SolutionFound event. |
| Population | Represents a set of potential solutions (Genes) with associated fittness and evaluation data. |
| SteadyStateGA | Implementation of Steady-State (Generational Gap) algorithm. |
| Delegate | Description |
|---|---|
| GeneticAlgorithm.NewGenerationHandler | Represents the method that will handle the NewGeneration event of GeneticAlgorithm class. |
| GeneticAlgorithm.SolutionFoundHandler | Represents the method that will handle the SolutionFound event of GeneticAlgorithm class. |
| Enumeration | Description |
|---|---|
| GenerationalGA.GASelectionType | Defines implemented selection algorithms. |
| GeneticAlgorithm.GAOptimizationType | Specifies the problem optimization type. |