Manual material handling (MMH) tasks were evaluated and compared under different lifting conditions. For the theoretical evaluations, a two-dimensional sagittally symmetric human-body model was established to compute the moment and joint load time histories for MMH tasks for a variety of different lift specifications and constraints such as lifting durations, loads, and modes. Nonlinear control techniques and genetic algorithms were utilized in the optimizations to explore optimal lifting patterns. Since the kinetic measures such as joint moments are vital metrics in the assessment of the likelihood of injury, the simulation results obtained may be compared using these metrics for each lift type, so that the superiority of a lifting method or protocol relative to another may be determined.