Population processing--a powerful class of parallel algorithms.
We present a model of optimization of cost functions by a population of parallel processors and argue that especially diploid recombination of gene strings is a promising recipe for optimization which nature proliferates. Based on a simulated evolutionary search strategy diploidy is introduced as a means for maintaining variability in computational problems with large numbers of local extrema. A differentiation into genotypes and phenotypes is performed. The applied strategy is compared to some traditional algorithms simulating evolution on the basis of two sample cost functions.
Algorithms↗