Day 12: Genetic Algorithms’ Elitism for Evolution Survival of the Fittest
Natural selection favors the survival of the fittest, but evolution in the wild is not always efficient. In genetic algorithms, we can bias the process toward faster convergence by deliberately preserving top-performing individuals across generations. This technique is known as elitism, and it is one of the simplest yet most effective strategies for enhancing GA performance.
Today’s post focuses on applying elitism in a C# genetic algorithm to ensure that the best solutions are never lost. We will define elitism, explain its impact on the evolutionary process, and demonstrate how to implement it cleanly and effectively.