This paper deals with evolutionary programming for optimization problems. The algorithm manipulates chromosomes of which genotypes contains heterogeneous data (integer and float numbers), depending on each other. Moreover, length of the chromosomes is different within a common evolution. The evolutionary algorithm is described and optimization results are compared to the previously implemented methodology. Stability of the algorithm facing a change of problem dimensions is also tested and discussed.
['Sophie Sakka']
Heterogeneous variable-length genotypes for evolutionary optimization