Genetic algorithms (GAs) are a type of evolutionary algorithm used for optimization and search problems. Inspired by the process of natural selection, GAs use techniques such as mutation, crossover, and selection to evolve solutions to complex problems. These algorithms begin with a randomly generated population of solutions and iteratively improve them based on a fitness function until an optimal or satisfactory solution is found.
