This paper investigates the problem of route planning for rechargeable unmanned aerial vehicles (UAV) under the mission time constraint in cases where more than one trip per round is required due to limited battery capacities. The goal is to determine the number of UAVs to be deployed and the flying paths that minimize the total mission cost. Unlike previous works, the electric cost incurred by UAV recharging proportional to actual flying distances is incorporated into our model. The problem is formulated as a mixed-integer programming model to minimize the sum of electric charging cost, the UAV usage cost, and the penalty cost from the violation of the mission time constraint. Extensive numerical experiments are conducted to examine the integrity and performance of the proposed model under various model parameters and deployment scenarios in grid areas and a real terrain area. The optimal solutions can be obtained for small-scale problem instances in a reasonable runtime. For large-scale problems, only feasible solutions can be obtained due to limited computational resources.

中文翻译：

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充电和任务时间约束下的无人机航路规划

本文研究了在任务时间限制下，由于电池容量有限，每轮需要超过一次行程的可充电无人机（UAV）的路线规划问题。目标是确定要部署的无人机数量和最小化总任务成本的飞行路径。与以前的工作不同，无人机充电所产生的与实际飞行距离成正比的电力成本被纳入我们的模型。该问题被表述为一个混合整数规划模型，以最小化充电成本、无人机使用成本和违反任务时间约束的惩罚成本之和。进行了广泛的数值实验，以检查所提出模型在网格区域和真实地形区域的各种模型参数和部署场景下的完整性和性能。对于小规模问题实例，可以在合理的运行时间内获得最优解。对于大规模问题，由于计算资源有限，只能得到可行的解决方案。