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It is widely recognized that the number of switching turn-on/off actions is proportional to the switching loss. However, Y-Matrix Modulated (YMM) based Modular Multi-level Converter (MMC) has a significantly larger number of switching actions in each fundamental cycle compared to phase shift and level shift modulation methods in order to achieve self-voltage balancing. Given the large amount of switching patterns provided by high level MMCs, the analytical methods make it hard to find the optimal switching scheme. In this paper, a general approach for finding the N-level switched capacitor MMC (SC-MMC) optimal switching scheme using Genetic Algorithm (GA) is proposed. The main objective is to propose a heuristic method to minimize the switching actions with self voltage balancing for SC-MMC. Case studies have been implemented on four-level, eleven-level, and fifty-level SC-MMCs. The optimal solution has also been evaluated in terms of the computational complexity, capacitor voltage ripple, and total harmonic distortion (THD) to validate the effectiveness of the proposed method. The simulation results demonstrate the computational efficiency of the proposed algorithm in comparison to the analytical method. Moreover, the proposed algorithm can achieve a substantial 22% reduction in switching actions compared to the original switching pattern.