Dynamic trait expression for multiploid individuals of evolutionary algorithms

The use of multiploid structures for individuals in evolutionary algorithms has been shown to have the advantage of including redundant information, increasing population diversity and in some cases improving non-stationary function optimisation performance. These advantages can translate into improved avoidance of premature convergence and an ability to cope with complex problems. However, as multiple information for the same trait is available, a method of gene selection or activation is required. This paper describes a dynamic decision method for gene selection, presents proof of concept results for this type of structure and outlines proposed benefits and applications