Genetic algorithms (GAs) [28] are general-purpose stochastic
search techniques based on natural genetic and evolution mechanisms. They combine the survival of the fittest law with a structured, yet randomized information exchange among a population of artificial creatures, resembling samples of the search space of the problem in hand. During the last two decades, GAs
have been successfully applied to several complex optimization
problems in business, science, and engineering.