Studies on standard many-objective optimisation problems have indicated that multi-objective optimisation algorithms struggle to solve optimisation problems with more than three objectives, because many solutions become dominated. Therefore, the Paretodominance relation is no longer efficient in guiding the search to find an optimal Pareto front for many-objective optimisation problems. Recently, a partial dominance approach has been proposed to address the problem experienced with application of the dominance relation on many objectives. Preliminary results have illustrated that this partial dominance relation has promise, and scales well with an increase in the number of objectives. This paper conducts a more extensive empirical analysis of the partial dominance relation on a larger benchmark of difficult many-objective optimisation problems, in comparison to state-of-the-art algorithms. The results further illustrate that partial dominance is an efficient approach to solve many-objective optimisation problems.