Real-world problems often involve balancing multiple goals, which can be tricky due to uncertainties. A new method has been developed to compare potential solutions in these situations, taking into account uncertainties that can follow any type of distribution. This method helps find better solutions more efficiently than existing techniques, making it easier to tackle complex problems with multiple uncertain objectives.