A genetic algorithm makes uses of techniques inspired from evolutionary biology such as
- Selection(Reproduction),
- Mutation,
- Inheritance
- Cross Over(recombination) to solve a problem.
The most commonly employed method in genetic algorithms
- create a group of individuals randomly from a given population.
- The formed individuals are evaluated with the help of the evaluation function provided by the programmer.
- Individuals are then provided with a score which indirectly highlights the fitness to the given situation.
- The best two individuals are then used to create one or more offspring, after which random mutations are done on the offspring.
- Depending on the needs of the application, the procedure continues until an acceptable solution is derived or until a certain number of generations have passed.
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