  In this paper, we deal with the Front Steepest Descent algorithm for
multi-objective optimization. We point out that the algorithm from the
literature is often incapable, by design, of spanning large portions of the
Pareto front. We thus introduce some modifications within the algorithm aimed
to overcome this significant limitation. We prove that the asymptotic
convergence properties of the algorithm are preserved and numerically show that
the proposed method significantly outperforms the original one.
