Genetic Algorithms

Optimization techniques inspired by evolution and natural selection. Like breeding the best traits in animals, genetic algorithms create a 'population' of potential solutions, combine the best ones, introduce random mutations, and repeat over generations. They're particularly useful for complex optimization problems where traditional methods struggle, like designing efficient networks or scheduling.