关键词:量子计算; 量子遗传算法; 优化算法
Improved quantum genetic algorithm with double chains and its application
XU Shao-hua, XU Chen, HAO Xing, WANG Ying, LI Pan-chi
(School of Computer & Information Technology, Daqing Petroleum Institute, Daqing Heilongjiang 163318, China)
Abstract:Aiming at the problems that how to keep population diversity and improve optimization efficiency in double chains quantum genetic algorithm, this paper proposed three improvements. Firstly, by adding the constant factor to the trigonometric expressions of quantum bit probability amplitudes, performed the search in a number of trigonometric functions cycle at the same time, which enhanced the optimization efficiency of the proposed algorithm. Secondly, the mutation strategy applying the single bit quantum Hadamard gates enhanced the diversity of population. Thirdly, enhanced the adaptability of the proposed algorithm by redesigning the step function of rotation angle of quantum rotation gates, and this also avoided the oscillation effectively. Finally, with application of function extremum optimization with multi-variables, the simulation results show that the three improvements are efficient.......