| GeneticSharp.Domain Namespace | GeneticSharp |
GeneticSharp domain model.
Classes
| Class | Description | |
|---|---|---|
|
GeneticAlgorithm |
A genetic algorithm (GA) is a search heuristic that mimics the process of natural selection.
This heuristic (also sometimes called a metaheuristic) is routinely used to generate useful solutions
to optimization and search problems.[1] Genetic algorithms belong to the larger class of evolutionary
algorithms (EA), which generate solutions to optimization problems using techniques inspired by natural evolution,
such as inheritance, mutation, selection, and crossover.
Genetic algorithms find application in bioinformatics, phylogenetics, computational science, engineering,
economics, chemistry, manufacturing, mathematics, physics, pharmacometrics, game development and other fields.
 Wikipedia |
Interfaces
| Interface | Description | |
|---|---|---|
|
IGeneticAlgorithm |
Defines a interface for a genetic algorithm.
|
Enumerations
| Enumeration | Description | |
|---|---|---|
|
GeneticAlgorithmState |
The possible states for a genetic algorithm.
|