Study on Delivery of Military Drones and Transport UGVs with Time Constraints Using Hybrid Genetic Algorithms

Jeonghun Lee, Suhwan Kim
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Abstract

This paper studies the method of delivering munitions using both drones and UGVs that are developing along with the 4th Industrial Revolution. While drones are more mobile than UGVs, their loading capacity is small, and UGVs have relatively less mobility than drones, but their loading capacity is better. Therefore, by simultaneously operating these two delivery means, each other's shortcomings may be compensated. In addition, on actual battlefields, time constraints are an important factor in delivering munitions. Therefore, assuming an actual battlefield environment with a time limit, we establish delivery routes that minimize delivery time by operating both drones and UGVs with different capacities and speeds. If the delivery is not completed within the time limit, penalties are imposed. We devised the hybrid genetic algorithm to find solutions to the proposed model, and as results of the experiment, we showed the algorithm we presented solved the actual size problems in a short time.
基于混合遗传算法的军用无人机和运输ugv交付研究
本文研究了伴随第四次工业革命发展的无人机和ugv的弹药投送方法。无人机的机动性比ugv强,但其装载能力较小,ugv的机动性相对不如无人机,但装载能力更好。因此,通过同时操作这两种交付方式,可以弥补彼此的不足。此外,在实际战场上,时间限制是运送弹药的一个重要因素。因此,假设一个有时间限制的实际战场环境,我们通过使用不同容量和速度的无人机和ugv来建立最小化交付时间的交付路线。如果未在规定期限内完成交付,将受到处罚。我们设计了混合遗传算法来求解所提出的模型,实验结果表明,我们提出的算法在短时间内解决了实际的尺寸问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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