Genetic Algorithms

Genetic Algorithms (GAs) are optimization techniques inspired by the process of natural selection. They use mechanisms such as selection, crossover, and mutation to evolve solutions to problems over successive generations. GAs are particularly effective in searching large and complex spaces where traditional optimization methods may struggle. Common use cases include optimization problems in engineering, finance, and artificial intelligence, such as feature selection, scheduling, and game strategy development.