They encode the parameters of a problem in a single-stranded or haploid binary string. However, most haploid organisms in the biological world are simple lifeforms such as bacteria. More complex lifeforms such as plants, animals, and humans rely on a diploid chromosome, which contains homologous chromosome pairs at each locus. Overdominance refers to the situation where an individual with different alleles at a location has higher fitness than individuals with the same allele at that location.
Biological models show that overdominance can maintain diversity at that location.
The primary motivation for incorporating diploidy and dominance into GAs is to increase population diversity and thus avoid premature convergence to a suboptimal solution. In a multimodal fitness landscape, this added diversity may enable a GA to avoid convergence to local optima. This talk will discuss application of diploidy to genetic algorithms. Previous empirical work has shown that methods based on artificial diploidy can help to increase population diversity. We discuss a new method of applying diploidy to genetic algorithms that includes overdominance.