Abstract: Aiming at the existing quantum ant colony algorithm which constructs and updates two pheromone chains but selects only one chain for optimizing operation, a double-chain quantum-inspired ant colony system is put forward in this paper. The solution space of the algorithm is constructed with two chains which are cosine and sine, and strategies of the city nodes selection of the ants on different chains are given. The range of phase angle of the quantum bit of pheromone and the range of max-min quantum pheromone are defined. The decay and reinforcement strategies of quantum pheromone based on quantum rotation gate are given, and a smoothing mechanism of pheromone is used to improve the performance of the algorithm. Finally, the algorithm is validated, compared and analyzed with the Traveling Salesman Problem（TSP）, and the results of simulation show that the double-chain quantum-inspired ant colony system is stable and excellent searching ability.

Key words: quantum-inspired ant colony system, double-chain, quantum rotation gate, Traveling Salesman Problem（TSP）

摘要： 针对现有量子蚁群算法构造、更新两条信息素链，但只选择一条链进行寻优操作的问题，提出了一种双链量子蚁群系统。该算法采用余弦和正弦双链蚂蚁寻优构造解空间，针对不同链上蚂蚁的特征构造了不同的路径选择策略；定义了信息素量子比特相位角的范围和量子信息素最大最小区间，给出了基于量子旋转门的量子信息素挥发与增强策略，运用了一种信息素的平滑机制以提高算法的性能；最后结合TSP算例对算法进行验证、比较与分析，仿真结果表明双链量子蚁群系统具有算法稳定、寻优能力强的特点。

关键词: 量子蚁群, 双链, 量子旋转门, 旅行商问题