Parallel robots, owing to their increased stiffness, accuracy, and compactness, are preferred over their serial counterparts in applications involving higher torques and precision such as robot-assisted physical therapy. However, their design is complex and calls for obtaining a tradeoff between several conflicting objectives such as the minimization of actuator forces versus the maximization of workspace while maintaining a close to unity condition number, etc. While evolutionary algorithms have been proposed in the literature for simultaneous optimization of many objectives, they have been found to be inefficient in dealing with a large number of objectives. We propose a fuzzy logic-based sorting approach in this paper which effectively replaces the concept of nondominated sorting and provides a better discrimination between solutions and clear termination logic. The proposed sorting algorithm has been evaluated against the existing nondominated sorting genetic algorithm II in the pretext of design optimization of a parallel ankle rehabilitation robot. The proposed fuzzy-based approach is able to provide a better discrimination among solutions and, thereby an improved parallel ankle robot design.