一种定向式挖掘的连续域蚁群算法  

Directional Mining Continuous Domain Ant Colony Algorithm

作　　者：刘文[1,2] 

机构地区：[1]大连理工大学计算机科学与技术学院,大连116024 [2]新疆工程学院电气工程系,乌鲁木齐830011

出　　处：《计算机科学》2013年第12期292-294,共3页Computer Science

基　　金：新疆维吾尔自治区高校科研计划(XJEDU2010S48)资助

摘　　要：针对蚁群算法在求解连续域优化问题时存在复杂度较大、迭代次数较长等问题,提出了一种用于连续域寻优的改进蚁群算法。改进的蚁群算法通过对解空间定向式挖掘来实现全局快速搜索。给出了新算法仿真实验步骤,并将改进后的蚁群算法与其他连续域蚁群算法以及其他智能优化方法进行仿真对比实验。详细的测试结果表明,改进后算法具有优良的全局优化性能,收敛速度也有很好的提升。An improved ant colony algorithm for continuous domain optimization was raised in order to solve the prob- lems that there is great complexity when ant colony algorithm solves the optimization problem of continuous domain and a large number of iterations. The improved ant colony algorithm achieves global rapid search by directionally digging the solution space. This paper presented a new algorithm simulation steps, and carried out simulation comparison experi- ments of the improved ant colony algorithm and the ant colony algorithm of continuous domain and other intelligent op- timization methods. Detailed test results show that the improved algorithm has excellent global optimization quality, and convergence rate also improves a lot.

关 键 词：蚁群算法 连续域 进化算法 定向挖掘 优化 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]