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The proper design of RF pulses in magnetic resonance imaging has a direct impact on the quality of acquired images. Several techniques have been proposed to obtain the RF pulse envelope given the desired slice profile. Unfortunately, these techniques do not take into account the limitations of practical implementation such as limited amplitude resolution. Moreover, implementing constraints for special RF pulses on most techniques is not possible. In this work, we propose an approach for designing optimal RF under theoretically any constraints. The new technique poses the RF pulse design problem as a combinatorial optimization problem and uses efficient techniques from this area to solve this problem. In particular, an objective function is proposed as the norm of the difference between the desired profile and the one obtained from solving the Bloch equations for the current RF pulse design values. Two global optimization techniques were implemented using genetic algorithms and simulated annealing. The results show a significant improvement over conventional design techniques and suggest the practicality of using the new technique for clinical use.