基于量子进化算法和蝙蝠算法,提出一种新型优化算法——量子蝙蝠算法。该算法采用量子位对蝙蝠的位置进行编码,用量子旋转门实现对蝙蝠最优位置的搜索,用量子非门实现蝙蝠的变异以避免早熟收敛。通过对典型复杂函数的实验和与其他算法的比较,结果表明,该算法能够有效避免局部最优,全局寻优能力强。
This paper proposes a novel optimization algorithm-quantum bat algorithm, which is based on quantum evolution and bat algorithm. The algorithm uses quantum bit to encode the position of the bat, searches the optimal solution with quantum rotation gate, adopts the quantum non-gate to realize quantum mutation to avoid premature convergence. The results of experiments on typical complex function optimization and the comparison with other algorithms show that the algorithm can avoid the local optimum and has a strong capability for the global optimium.