Applying OpenMP-based parallel implementations of NSGA-II and SPEA2 to study phylogenetic relationships

Throughout the years, biological processing demands have been addressed by relying on the design of algorithmic approaches for parallel architectures. By taking advantage of multicore processor systems, we can deal with the main sources of complexity which explain the NP-hard nature of multiple problems in computational biology. In this work, we address the inference of phylogenetic topologies by using two multiobjective metaheuristics: Fast Non-Dominated Sorting Genetic Algorithm and Strength Pareto Evolutionary Algorithm 2. The additional complexity introduced by the multiobjective formulation of the problem motivates that parallel designs of these algorithms must be undertaken. For this purpose, OpenMP-based implementations of these two metaheuristics are applied. To evaluate the performance of these approaches, a comparative study has been conducted by performing experimentation on four nucleotide data sets. Our experiments suggest the relevance of these parallel algorithmic designs, improving the phylogenetic results reported by other multiobjective tools in reduced execution times.