基于改进的文化蚁群算法求解最优路径问题研究  

Research on an Improved Cultural Ant Colony Algorithm for Solving the Optimization Route

作　　者：薛小虎[1] 南振岐 赵文杰[3] 

机构地区：[1]兰州交通大学数理与软件工程学院,甘肃兰州730070 [2]兰州南特数码科技股份有限公司,甘肃兰州730010 [3]西北师范大学数学与信息科学学院,甘肃兰州730070

出　　处：《佳木斯大学学报（自然科学版）》2011年第1期54-57,共4页Journal of Jiamusi University：Natural Science Edition

摘　　要：针对传统方法不能够有效的求解GIS最优路径问题,在文化算法的基础上提出了一种基于实际路况求解两地之间最优距离的蚁群优化算法.引入了表示天气、路况、驾驶员个人偏好等诸多不确定因素,并将改进的蚁群算法融入到文化算法当中,使蚁群算法具有群体空间和信仰空间并行进化的机制.群体空间采用改进的最大最小蚁群算法,从而有效的提高算法最优解的搜索能力和速度.通过模拟计算结果表明改进的算法求解实际最优路径在速度和精度上优于传统最优路径算法.In order to get the best road about GIS that traditional method cant calculate effectively,an improved Ant Colony Optimization algorithm for solving optimization Route which is from one site to another in our city was proposed based on cultural algorithm.The uncertain factors were defined to represent the effect of weather,condition of road,preference of driver etc.The improved Ant Colony Algorithm（ACA） was integrated into cultural algorithm to get new algorithm which includes parallel evolution both the population space and the belief space.The population space adopted improved Max-Min Ant System（MMAS） to improve the speed of searching the optimization result.The experiment result proved that the improved cultural Ant Colony Algorithm is better than the traditional optimization algorithm in the respects of speed and precision.

关 键 词：蚁群算法 文化算法 最短路径 GIS 

分 类 号：TP301.6[自动化与计算机技术—计算机系统结构]