摘要
研究两地间时间最优路径的问题。针对基本蚁群算法搜索的盲目性,迭代时间长,易陷局部最优解的问题,造成寻找最优路径困难。为提高寻优效率,提出一种改进的蚁群算法来求解问题。在方案中引入阀值排序算法对搜索路径进行优化,解决了蚁群算法前期搜索路径的盲目性问题。改进的蚁群算法加快了收敛速度,并提高了稳定性。经仿真证明:改进蚁群算法性在减少算法的迭代次数和提高解的稳定性方面有了较大的提高,并且能很好的用于求解路径时间最优问题。
Optimization problem of the time optimal path between the two locations was studied. For the blindness of basic ant colony algorithm, long iterate time and easy to trap into a local optimal solution, an improved intelligent ant colony algorithm was proposed to improve the problems and increase its operational efficiency. In the program, threshold sort algorithm was introduced to optimal search path, the problem of slow convergence was solved, which is caused by blindness of ant colony algorithm convergence in the early time. The improved ant colony algorithm can speed up the convergence speed and improve the stability. The simulation result indicates that improved ant colony algorithm reduces the iterative times, greatly improves the stability of the solution, and is better for the time optimal oroblem.
出处
《计算机仿真》
CSCD
北大核心
2012年第6期223-227,共5页
Computer Simulation
基金
辽宁省教育厅高等学校科研项目(2009A349)
辽宁省教育厅基金项目(2009A350)
关键词
蚁群算法
时间最优
期望因子
阀值排序算法
Ant colony algorithm
Time optimal
Expected factor
Threshold sorting algorithm