Abstract
Memetic Algorithms (MAs) are population-based metaheuristics composed of an evolutionary framework and a set of local search algorithms which are activated within the generation cycle of the external framework, see [376]. The earliest MA implementation has been given in [621] in the context of the Travelling Salesman Problem (TSP) while an early systematic definition has been presented in [615]. The concept of meme is borrowed from philosophy and is intended as the unit of cultural transmission. In other words, complex ideas can be decomposed into memes which propagate andmutate within a population.Culture, in this way, constantly undergoes evolution and tends towards progressive improvements. Strong ideas tend to resist and be propagated within a community while weak ideas are not selected and tend to disappear. In the metaphor, the ideas are the search operators: the fittest tend to be employed while the inadequate ones are likely to disappear.