量子谐振子蚁群算法  

Ant colony optimization of quantum harmonic oscillators

作　　者：秦永波[1,2] 王鹏[3] 肖黎彬[3] 江炳坤[1,2] 任超[3] 孟玉[1,2] 

机构地区：[1]中国科学院成都计算机应用研究所,成都610041 [2]中国科学院研究生院,北京100049 [3]成都信息工程学院软件学院,成都610025

出　　处：《计算机应用》2011年第A02期54-56,69,共4页journal of Computer Applications

基　　金：国家自然科学基金资助项目(60702075);四川省青年科学基金资助项目(09ZQ026-068)

摘　　要：通过分析目前蚁群算法存在的问题和改进算法的优点,发现量子谐振子系统物理特性能够保证算法最终的收敛性。通过量子谐振子高能态到低能态的转变过程和信息素的增加过程相对应,从而更新信息素,在物理上给算法提供了理论依据。通过量子旋转门改变城市转移规则,通过泡利矩阵变异使蚂蚁有更广阔的空间。综合量子谐振子以上的优点,提出了量子谐振子蚁群算法,并在旅行商问题(TSP)上取得了较好的寻优路径。The authors analyzed the current problems of ant colony algorithm and the advantages of improved algorithm,and then found that the physical properties of quantum harmonic oscillators would guarantee the convergence of final algorithm.Changing process of the quantum harmonic oscillators from high energy state to low energy state and increment of pheromone had a corresponding relationship,and thereby updated pheromone,and physically it provided the algorithmic theoretical basis.Quantum rotation door changed the transfer rules of city.Mutations by Pauli matrix allowed ants have a wider space.Integrating the above advantages of quantum harmonic oscillator,the authors proposed a quantum harmonic oscillator ant colony algorithm,and achieved better optimization path in the Traveling Saleman Problem（TSP） problems.

关 键 词：蚁群算法 量子谐振子 旋转门 泡利矩阵 信息素 

分 类 号：TP301.6[自动化与计算机技术—计算机系统结构]