Multi-objective optimization (MOO) has emerged recently as a useful technique in the design and planning of engineering systems because it allows identifying alternatives leading to significant environmental savings. MOO models typically contain an infinite number of Pareto solutions, from which decision-makers should choose the best one according to their preferences. An approach is here presented that identifies and retains for further inspection a reduced set of Pareto solutions showing better overall performance. The capabilities of our approach are illustrated through its application to the design of reverse osmosis desalination plants considering simultaneously the unitary production cost and a set of environmental impacts in several damage categories. Our method reduces significantly the number of Pareto points, thereby facilitating the decision-making process in MOO. (C) 2015 Elsevier Ltd. All rights reserved.