Day 6: Roulette, Tournaments, and Elites: Exploring Selection Strategies
Once you’ve calculated the fitness of each chromosome in your population, the next step in the genetic algorithm lifecycle is selection—deciding which chromosomes get to reproduce and which are left behind.
Selection strategies play a crucial role in balancing exploration (searching new areas of the solution space) and exploitation (refining known good solutions). Choosing the right strategy affects the convergence speed and the overall effectiveness of your genetic algorithm.
Today, we’ll explore the most common selection strategies: roulette wheel selection, tournament selection, and elitism. We’ll compare them and implement each one in C#.