一种改进的量子蚁群算法及其应用  

AN IMPROVED QUANTUM ANT COLONY ALGORITHM AND ITS APPLICATION

作　　者：赵俊生[1] 李跃光[1] 张远平[2] 

机构地区：[1]甘肃民族师范学院计算机科学系,甘肃合作747000 [2]兰州理工大学计算机与通信学院,甘肃兰州730050

出　　处：《计算机应用与软件》2010年第7期133-135,216,共4页Computer Applications and Software

基　　金：甘肃教育厅科研基金项目(0614B-03)

摘　　要：将量子群进化算法(QEA)与蚁群系统(ACS)进行融合,提出一种新的量子蚁群算法(QACA)。该算法的核心是在蚁群系统(ACS)中引入量子算法中的量子的态矢量和量子旋转门来分别表示和更新信息素,从而在全局寻优能力和种群多样性方面比蚁群算法有所改进。结合旅行商问题(TSP),对算法进行了测试,得到了与现有文献结果相同或更好的解,表明该算法具有较强的问题求解能力。A new algorithm,quantum ant colony algorithm（QACA） is presented in this paper based on combining quantum evolutionary algorithm（QEA） with ant colony system（ACS）.The core of the QACA is that the state vector and quantum rotation gate of the quantum in QEA are introduced into ACS to represent and update the pheromone respectively,so it has an improvement in global search ability and population diversity compared with ant colony algorithm.The QACA is tested in combination with travelling salesman problems（TSP）,the solutions same as or better than the solutions given in TSPLIB are obtained,they demonstrate that it has a quite strong ability in problem solving.

关 键 词：量子算法 量子进化算法 蚁群系统 量子蚁群算法 TSP 

分 类 号：TP301.6[自动化与计算机技术—计算机系统结构]