旅行优化器:通过蚁群和遗传进化优化旅行时间

上传者: 42162171 | 上传时间: 2022-12-13 14:03:57 | 文件大小: 11MB | 文件类型: ZIP
通过蚁群和遗传进化的旅行时间优化 在这个项目中,我解决了出租车的旅行时间优化问题。 可以将其称为“旅行推销员问题” ,这是众所周知的计算机科学问题。 目的是找到访问一组位置的最短路径。 对于此问题,需要优化技术来智能地搜索解空间并找到接近最优的解。 更具体地说,我首先使用XGBoost模型来预测每对上落地点之间的旅行时间。 然后,我使用了进化算法,即蚁群和遗传算法,为数据中的车辆找到了最佳的旅行路线。 可以在以下链接找到有关Medium的随附博客文章: 数据集 数据是已经下载到上的数据。 我有2016年黄色出租车,绿色出租车和出租汽车的月度数据。 该数据集具有11个属性的近150万个行程记录

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