基于改进蚁群算法的光纤光缆铺设路径规划

Path Planning of Fiber Optic Cable Laying Based on Improved Ant Colony Algorithm

利用蚁群算法精度高、速度快、易找到拟最优解等优点,使其与光纤光缆的铺设路径规划相结合,能大大解决光纤光缆铺设成本问题,但是基础蚁群算法存在随机性大、收敛速度慢等弊端,因此对蚁群算法进行改进。运用栅格法构造环境模型,引入环境因子来调整启发函数,增强了蚂蚁搜索的目的性,解决了随机性强的弊端。通过改进信息素挥发系数,增加初始阶段蚂蚁搜索的全局性,使收敛次数大大减少。最终仿真结果显示,改进后的蚁群算法,收敛速度明显增加,而且具有较强自适应能力,使光纤光缆的铺设成本大大降低。

Using the advantages of ant colony algorithm,such as high accuracy,fast speed,and it's easy to find the quasi-opti-mal solution,combined with the laying path planning of optical fiber and cable,it can greatly solve the problem of optical fiber and cable laying cost.The basic ant colony algorithm has drawbacks such as high randomness and slow convergence speed.Therefore,the algorithm is improved.Modeling using grid method,and environmental factors are introduced to adjust the heuristic function,which enhances the purpose of ant search and solves the shortcomings of strong randomness.By improving the pheromone volatiliza-tion coefficient,Increase the searchability of the ant colony at the beginning,so that the convergence time is short.The results show that the improved algorithm has short convergence time and strong adaptability,which greatly reduces the cost of fiber optic cable laying.