优化蚁群算法的智能物资农机路径规划

Path planning of intelligent material agricultural machinery based on optimized ant colony algorithm

针对智能物资农机在运输过程中需要考虑不同路段中运输速度、运输时间及提高价值收益等问题,提出一种优化蚁群算法的智能物资农机路径规划策略。首先对农田地图栅格化与膨胀化处理,修正蚁群算法的寻优环境;再对蚁群算法进行优化处理,添加速度影响因子;然后设置合理的初始值、不同栅格的速度及不同栅格路段的收益等,对比找到收益最高的路径;最后通过大量仿真实验验证了所提算法更有优势,迭代次数降低,用时更短,收益更高。

In order to solve the problems of transportation speed,transportation time and value improvement in different road sections in the transportation process of intelligent materials agricultural machinery,a path planning strategy of intelligent materials agricultural machinery based on optimized ant colony algorithm was proposed.Firstly,the farmland map was rasterized and expanded,and the optimization environment of ant colony algorithm was corrected.Then,the ant colony algorithm was optimized and the speed influence factor was added.The reasonable initial value,the speed of different grids and the revenue of different grid sections were set to find the path with the highest revenue by comparison.Finally,a large number of simulation experiments verified that the proposed optimization algorithm had more advantages,the number of iterations was reduced,the time was shorter,and the revenue was higher.