人工蜂群演算法(ArtificialBee Colony , ABC)為近年來熱門的演化式計算， 其優點為參數設定簡單、穩定性高、收斂速度快及求解的準確度高；但是仍存有 著過早收斂及可能陷入區域最佳解的問題。特別在求解高維度函數問題，更是容 易陷入區域最佳解，故本研究針對高維度函數問題，提出以差分演算法突變策略 來改良蜂群演算法，實驗結果顯示可提升蜂群演算法在高維度函數問題的求解精確度。

Artificial Bee Colony algorithm (ABC) is a novel optimization algorithm in recent years. This method has a good investigation capability, and it is also simple and easy to implement. Though ABC has many advantages, there are still some drawbacks, such as premature convergence and falling into local optimal solutions, especially for high dimensional functions. In this study, we propose the mutation strategy for solving these problems. This approach can enhance the solution accuracy, and also increase the performance for high dimensional problems.