摘要
针对旅行商问题(TSP),提出了一种新的混合量子优化算法——量子蚁群算法.量子蚁群算法采用量子比特的概率幅表示蚂蚁的当前位置,采用量子旋转门更新蚂蚁的位置,选取国际通用的TSP实例库中多个实例进行测试.仿真实验表明,该算法具有很好的精确度和鲁棒性,可使搜索空间加倍,比传统的蚁群算法具有更好的种群多样性.
Based on the combination of the quantum theory and ant colony optimization, a novel algorithm, the quantum ant colony algorithm, was proposed. Ants＇s positions were represented by a group of quantum bits and the quantum rotation gates were designed to update the ants＇ positions for enabling the ants＇ movements. The classical TSP was successfully solved by using the quantum ant colony algorithm, taking series of typical instances as the examples. The computational results show the effectiveness and robustness of the algorithm in numerical simulations. The algorithm can find the satisfactory solutions with a small size of populations and minimal relative error.
出处
《上海理工大学学报》
CAS
北大核心
2012年第4期355-358,共4页
Journal of University of Shanghai For Science and Technology
基金
国家自然科学基金资助项目(70871081)
河南省科技攻关重点资助项目(102102210022
122102210201)
关键词
量子优化
蚁群算法
量子蚁群算法
旅行商问题
quantum optimization； ant colony algorithm； quantum ant colony algorithm； traveling salesman problem（TSP）；
