Genetic algorithms (GA) are a computational paradigm inspired by the mechanics of natural evolution, including survival of the fittest, reproduction, and mutation.
Surprisingly, these mechanics can be used to solve (i.e. compute) a wide range of practical problems, including numeric problems. Concrete examples illustrate how to encode a problem for solution as a genetic algorithm, and help explain why genetic algorithms work.
Genetic algorithms are a popular line of current research, and there are many references describing both the theory of genetic algorithms and their use in practical problem solving.