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A Note on Integer Programming Formulations of the Real-Time Optimal Scheduling and Flight Path Selection of UAVs

机译:关于无人机实时最优调度与飞行路径选择的整数规划公式的注记

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摘要

In recent years, considerable attention has been given to research on various aspects of unmanned aerial vehicles (UAVs) applications. UAVs are currently used for various military and civilian missions in the air, sea, space, and on the ground. In two recent papers, Shima (2007) and Kim (2007) considered closely similar m-UAV problems. In Shima (2007), the problem is considered with each target being served by only one UAV to minimize the total travel distance across all UAVs (called load balancing), however, in Kim (2007), the problem is considered with maximum number of targets that each UAV can serve with the objective of minimizing load balancing. Kim presented mixed integer linear programming (MILP) formulations of the load balancing problem both for when the UAVs return to their original depot and when they do not. Shima presented a combinatorial optimization formulation of their model with a branch-and-bound solution procedure. The MILP formulation of the load balancing problem is also adaptable to Shima 's problem. However, there are major inefficiencies with the MILP formulation presented in Kim 's model. In fact, The MILP formulations presented in Kim are highly complicated with huge number of variables and constraints making them impractical for applications. The purpose of the present note is to provide explicit MILP formulations that dramatically reduce the number of variables and the number of constraints for variety of UAV tour assignment problems including the two models mentioned above and via simulation we show significance of these new formulations.
机译:近年来,人们对无人飞行器(UAV)应用的各个方面的研究给予了极大的关注。无人机目前用于空中,海上,太空和地面的各种军事和民用任务。 Shima(2007)和Kim(2007)在最近的两篇论文中考虑了非常相似的m-UAV问题。在Shima(2007)中,考虑到每个目标仅由一架无人机服务的问题,以最小化所有无人机之间的总行驶距离(称为负载平衡),但是,在Kim(2007)中,考虑到该问题的最大数量目标是每个UAV可以服务,以最小化负载平衡为目标。 Kim提出了混合整数线性规划(MILP)公式,说明了无人机何时返回原始仓库以及何时不返回原始仓库。 Shima提出了带有分支定界求解程序的模型组合优化公式。负载平衡问题的MILP公式也适用于Shima的问题。但是,Kim模型中提出的MILP公式存在很多低效之处。实际上,Kim提出的MILP公式非常复杂,具有大量变量和约束,因此对于应用程序不切实际。本说明的目的是提供明确的MILP公式,可以显着减少各种无人机巡逻任务问题的变量数量和约束数量,包括上述两个模型,并且通过仿真,我们展示了这些新公式的重要性。

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