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针对量子进化算法求解二进制编码问题比较有效,而求解多进制编码问题则比较困难的情况,本文提出了一种多进制概率角复合位编码量子进化算法。该算法将量子进化算法中量子位的概率幅表示法转化为复合位的概率角表示法,采用随机观测方法得到观测个体,采用概率角增减对个体进行更新,该算法适用于采用任意进制编码的问题。实验表明,与量子进化算法和传统遗传算法相比,多进制概率角复合位编码量子进化算法在适用范围、搜索能力和运算速度上具有较明显优势。
It is more effective to solve the binary coding problem based on quantum evolutionary algorithm, but it is more difficult to solve the multi-ary coding problem. In this paper, we propose a quantum-coded quantum evolutionary algorithm based on multi-bit probabilities. The algorithm transforms the probability representation of qubits in quantum evolution algorithm into the probabilistic angle representation of complex bits. The observed individuals are obtained by stochastic observation method, and the individuals are updated with the increase or decrease of probability angle. The algorithm is suitable for use in arbitrary hexadecimal Encoding problem. Experiments show that, compared with quantum evolutionary algorithm and traditional genetic algorithm, multi-scale probability angle complex code encoding quantum evolutionary algorithm in the scope of application, search capabilities and computing speed has obvious advantages.