一种改进的蚁群算法在垃圾运输问题中的应用  

Application of an Improved Ant Colony Algorithm to Litter Transportation Problem

作　　者：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,中国合作747000 [2]兰州理工大学计算机与通信学院,中国兰州730050

出　　处：《湖南师范大学自然科学学报》2010年第2期18-23,共6页Journal of Natural Science of Hunan Normal University

基　　金：甘肃省教育厅科研基金资助项目(0614B-03)

摘　　要：针对基本蚁群算法收敛速度慢、易陷于局部最优解等缺陷,将量子算法中的态矢量和量子旋转门引入到蚁群算法中,并分别表示和更新信息素,提出一种改进的蚁群算法——量子蚁群算法(QACA),使算法具有更好的种群多样性和全局寻优能力.结合垃圾运输问题,从数值计算上探索了改进的蚁群算法的优化能力,并与遗传算法和基本蚁群算法进行了对比,测试结果表明,改进算法获得的结果比遗传算法和基本蚁群算法更优,表明该算法是求解垃圾运输问题的一种有效算法.Aiming at the basic ant colony algorithm convergence slow and prone to plunge a partial basis,an improved Ant Colony algorithm—Quantum Ant Colony Algorithm（QACA） is proposed.The core is that Q-bit and quantum rotation gate adopted in QA are introduced into Ant Colony Algorithm to represent and update the pheromone respectively,so it has better diversity and global search capacity.The ability of optimization for the algorithm is tested through numerical computation,the experimental result demonstrates that the improved ant colony algorithm can get better solutions to the Litter Transportation Problem than genetic algorithm and basic ant colony algorithm,it indicates that the algorithm is effective to solve the Litter Transportation Problem.

关 键 词：量子算法 蚁群算法 遗传算法 垃圾运输问题 哈密顿圈 

分 类 号：TP273[自动化与计算机技术—检测技术与自动化装置]