This paper introduces a multiobjective optimization tool called MOSES (Multiobjective Optimization of Systems in the Engineering Sciences). This tool is a convenient testbed for analyzing the performance of new and existing multicriteria optimization techniques, and it is an effective engineering design teal. Two new multiobjective optimization techniques based on the genetic algorithm (GA) are introduced, and two engineering design problems are solved using them. These methods are based in the concept of minmax optimum, and can produce the Pareto set and the best trade-off among the objectives. The results produced by these approaches are compared to those produced with other mathematical programming techniques and GA-based approaches, showing the new techniques' capability to generate better trade-offs than the approaches previously reported in the literature.