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Dynamic Programming Approach for Drone Routes Planning

机译:无人机路线规划的动态编程方法

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This paper addresses the routes planning problem in a scenario where an UAV (Unmanned Aerial Vehicle) and a land-based transportation vehicle are used to deliver parcels to customer locations. We developed and implemented a solution based on the well-known Bellman-Held-Karp dynamic programming algorithm for the Travelling Salesman Problem that finds the least-cost routes for both the aircraft and the land-based transportation vehicle. We applied this algorithm to different, randomly selected commercial drones, with different maximum velocity and flight range, in order to select the best performing drone for the lowest price.
机译:本文解决了UAV(无人驾驶飞行器)和陆地运输工具将包裹提供给客户位置的场景中的路线规划问题。我们基于众所周知的Bellman-Hold-KARP动态编程算法开发并实施了一个解决方案,用于旅行推销员问题,该问题发现飞机和陆地运输车辆的最低途径。我们将该算法应用于不同,随机选择的商业无人机,具有不同的最大速度和飞行范围,以便为最低价格选择最佳的表现无人机。

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