Evolutionary Algorithms with Dissortative Mating on Static and Dynamic Environments

Evolutionary Algorithms (EAs) (Bäck, 1996) mimic the process of natural selection by recombining the most promising solutions to a problem from a population of individuals, each one representing a possible solution. There are several methods to select the individuals, but all of them follow the same general rule: good (or partially good) solutions must be chosen more often for recombination events than poorer solutions. In traditional Genetic Algorithms (GAs), for instance, the chromosomes are recombined via a crossover operator over a certain number of generations until a stop criterion is reached. The parents are selected according to their fitness values, that is, better solutions have larger probability to be chosen to generate offspring. By considering merely the quality of solutions represented in the chromosomes when selecting individuals for mating purposes, the traditional GAs emulate what, in nature, is called random mating (Roughgarden, 1979; Russel, 1998), that is, mating chance is independent of genotypic or phenotypic distance between individuals. However, random mating is not the sole mechanism of sexual reproduction observed in nature. Non-random mating, which encloses different kinds of strategies based on parenthood or likeness of the agents involved in the reproduction game, is frequently found in natural species, and it is believed to be predominant among vertebrates. Humans, for instance, mate preferentially outside their family tree: this non-random mating scheme is called outbreeding and has its opposite in inbreeding, a selection strategy where individuals mate preferentially with their relatives (Roughgarden, 1979; Russel, 1998). It is often stated that inbreeding decreases the genetic diversity in a population while outbreeding increases that same diversity (Russel, 1998). In addition, inbreeding will increase the normal rate of a harmful allele present in the family. If inbreeding is extensive and intensive, homozygosity will increase in frequency and the family experiences a growth in the genetic load (measure of all of the harmful recessive alleles in a population or family line) of the harmful allele. Assortative mating is another non-random mating mechanism, in which individuals choose their mates according to phenotypic similarities (Roughgarden, 1979; Russel, 1998). When similar individuals mate more often than expected by chance, we are in presence of positive assortative mating (or assortative mating in the strict sense). When dissimilar individuals O pe n A cc es s D at ab as e w w w .ite ch on lin e. co m