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针对具有连续解空间的数值函数优化问题,基于量子算法和实数编码进化算法的思想,提出一种新的相位角编码量子进化算法(PAQEA).算法的概率表达特性使得量子染色体能够以一定概率表达优化问题的所有可行解,结合动态量子旋转门实现染色体的进化,实现了算法局部搜索与全局搜索的平衡.理论分析证明了算法的全局收敛性.仿真结果表明,该算法适用于复杂数值函数优化问题,具有收敛速度快、搜索能力强和稳定性高的特点.
Aiming at the problem of numerical function optimization with continuous solution space, a new quantum phase-coded quantum evolution algorithm (PAQEA) is proposed based on the idea of quantum algorithm and real-coded evolutionary algorithm. The probability expression feature of the algorithm enables quantum chromosomes to be expressed with a certain probability And all the feasible solutions to the optimization problem are combined with the dynamic quantum revolving door to realize the evolution of the chromosomes and achieve the balance between the local search and the global search.The theoretical analysis proves the global convergence of the algorithm.The simulation results show that the algorithm is suitable for the optimization of complex numerical functions Problem, with the convergence speed, search ability and high stability.