一种量子模拟退火算法

Quantum simulated annealing algorithm

为扩展量子智能算法的研究领域,根据模拟退火算法的思想,提出量子模拟退火算法(QSA).定义了量子染色体相位邻域空间,缩小了算法搜索范围;引入信息熵的概念,避免了搜索的盲目性;给出一个量子的旋转角增量的表达式,简化了计算过程;采用Boltzmann概率分布原则接受新解,提高了算法的搜索性能;同时增加了量子变异操作和量子随机行为,可以防止算法早熟现象.研究结果表明:该算法具有较强的全局收敛性和搜索能力.

By combining quantum evolutionary algorithms and simulated annealing algorithm, this paper presented a quantum simulated annealing algorithm. In this algorithm, chromosome is encoded according to the phase; This study defined the phase neighborhood space and narrowed the scope of the algorithm search. The concept of information entropy was introduced to avoid searching blindness and the expression of the angle of rotation increments based on quantum revolving door was derived to simplify the calculation process. This study adopted the Boltzmann probability distribution principle to accept the new solution and improve the search performance of the algorithm; at the same time, the mutation operation and quantum random behavior were added to prevent the phenomenon of prematurity. It has proved the global convergence of the algorithm. Function optimization problem and PID controller parameter optimization problems were simulated. The results show that the algorithm has stronger global convergence and searching ability.