Phylogenetic Inference using Evolutionary Multi-objective Optimisation

Evolutionary relationships among species are usually (i) illustrated by means of a phylogenetic tree and (ii) inferred by optimising some measure of fitness, such as the total evolutionary distance between species or the likelihood of the tree (given a model of the evolutionary process and a data set). The combinatorial complexity of inferring the topology of the best tree makes phylogenetic inference an ideal candidate for evolutionary algorithms. However, difficulties arise when different data sets provide conflicting information about the inferred ‘best’ tree(s). We apply the techniques of multi-objective optimisation to phylogenetic inference. We present results for the simplest model of evolution and an artificially constructed four species problem.