Abstract: Conventional Quantum Genetic Algorithms（QGAs） are based on binary code so the computation process contains coding and decoding, which affects the efficiency. Real-coded Self-adaptive Quantum Genetic Algorithm（RSQGA） is proposed to solve this problem. Firstly, this algorithm introduces real number and quantum bit for coding, and neighbor operators of self-adaptive frequency are applied to update code. Then self-adaptive rotation angle strategy is used to update quantum bit string to keep the balance between exploration and exploitation. Finally, binary code genetic algorithm, binary quantum genetic algorithm and RQGA are tested by finding the optimal solution of Schaffer’f6 function, the result shows that RQGA performs best in convergence speed and accuracy.

Key words: real-coded, self-adaptive, quantum, genetic algorithm

摘要： 传统的量子遗传算法是基于二进制编码进行的，每次计算需要进行编码和解码操作，影响了算法的效率。针对这一问题，提出了实数编码的自适应量子遗传算法（RQGA）。首先运用实数和量子比特共同编码，并采用自适应频率的临近算符对编码进行更新，而后运用自适应转角策略更新量子比特串，以保证算法保持搜索性能和求解性能的平衡。最后分别采用二进制遗传算法、二进制量子遗传算法以及实数和量子比特共同编码的自适应量子遗传算法对Schaffer’f6函数进行测试对比，结果表明，实数和量子比特共同编码的自适应量子遗传算法无论在收敛速度还是收敛精度方面都体现了较好的优越性。

关键词: 实数编码, 自适应, 量子, 遗传算法