What is a genetic algorithm?
Genetic algorithms (GA) work by stimulating the logic of Darwinian selection, where only the best is selected for replication. Genetic algorithms can address complicated problems with many variables and possible outcomes by simulating the evolutionary process of “survival of the fittest” to reach a defined goal. They operate by generating many random answers to a problem, eliminating the worst and cross-pollinating better answers. Repeating this elimination and regeneration process gradually improves the quality of the answers to an optimal or near-optimal condition.
What are the stages of the genetic algorithm?
- Build and maintain a population of solutions to a problem.
- Choose the best solutions for recombination with each other.
- Use their offspring to replace poorer solutions.