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Priority-based assignment and routing of a fleet of unmanned combat aerial vehicles

机译:基于优先级的无人作战飞机编队和路线

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This paper considers the strategic routing of a fleet of unmanned combat aerial vehicles (UCAVs) to service a set of predetermined targets from a prior surveillance mission. Targets are characterized by their priority or importance level, and minimum and maximum service levels that, respectively, represent the lower bound of munitions for destruction and upper bound of munitions to limit collateral damage. Additional constraints to be respected are the payload capacities of the (possibly heterogeneous) UCAV fleet and the range based on fuel capacity and payload transported. The vital aspect of this paper is the integrated optimal utilization of available resources—weaponry and flight time—while allocating targets to UCAVs and sequencing them to maximize service to targets based on their criticality. The complexity of the problem is addressed through a decomposition scheme with two problems: a target assignment problem (modeled as a minimum cost network flow problem) and a vehicle routing problem, which in turn splits into multiple decision traveling salesman problems, one for each UAV. A Tabu search heuristic is developed to coordinate the two problems. Using test problems we establish the applicability of this approach to solve practical-sized problems.
机译:本文考虑了无人作战飞机(UCAV)机队的战略路线,以服务于先前的监视任务中的一组预定目标。目标的特点是其优先级或重要性级别,以及最低和最高服务水平,分别代表销毁弹药的下限和限制附带损害的弹药上限。需要考虑的其他约束是(可能是异构的)UCAV机队的有效载荷容量以及基于燃料容量和所运输有效载荷的范围。本文的重要方面是综合优化利用可用资源(武器和飞行时间),同时将目标分配给UCAV并对其进行排序,从而根据其关键程度为目标提供最大的服务。该问题的复杂性通过具有两个问题的分解方案来解决:目标分配问题(建模为最小成本网络流量问题)和车辆路线选择问题,后者又分解成多个决策旅行商问题,每个无人机一个。开发了禁忌搜索试探法来协调两个问题。使用测试问题,我们建立了该方法解决实际规模问题的适用性。

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