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Choosing the fastest route for urban distribution based on big data of vehicle travel time

机译:根据车辆行驶时间的大数据选择最快的城市配送路线

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With the increase in the number of urban cars, the city's road congestion is getting heavier and heavier. Often, we choose the shortest path to reduce costs and improve efficiency during logistics distribution, but now, in order to improve timeliness, it is necessary to choose the fastest route to deliver because of traffic jams. This paper proposes a method to select the fastest route based on big data of vehicle travel time, replacing distance values with travel time values, by using the improved Floyd algorithm. The method can improve the efficiency of urban distribution and reduce the time cost, and has significant application value.
机译:随着城市汽车数量的增加,城市的道路拥堵越来越严重。通常,我们选择最短的路径以降低成本并提高物流配送的效率,但是现在,为了提高及时性,由于交通拥堵,有必要选择最快的运输路线。提出了一种基于车辆行驶时间的大数据选择最快路径的方法,通过使用改进的弗洛伊德算法将距离值替换为行驶时间值。该方法可以提高城市配送效率,降低时间成本,具有重要的应用价值。

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