Optimizing Drone Logistics: A Scoring Algorithm for Enhanced Decision Making across Diverse Domains in Drone Airlines

Drones Pub Date : 2024-07-09 DOI:10.3390/drones8070307
Diyar Altinses, David Orlando Salazar Torres, Michael Schwung, Stefan Lier, Andreas Schwung
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Abstract

The complexities of decision-making in drone airlines prove to be pivotal and challenging as the dynamic environment introduces variability and many decisions are conventionally static. This paper introduces an advanced decision-making system designed for the multifaceted landscape of drone applications. Our proposed system addresses various aspects, including drone assignment, safety zone sizing, priority determination, and more. The scoring model enhances adaptability in real-time scenarios, particularly highlighted by the dynamic adjustment. Based on the scenario concerning the definition of the safety zone, we have successfully applied this method and evaluated all potential scores. The user-friendly and intuitive configuration further augments the system’s accessibility, facilitating efficient deployment. In essence, the proposed system stands as an innovative approach with decision-making paradigms in the dynamic landscape of drone operations.
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优化无人机物流:用于增强无人机航空公司跨不同领域决策的评分算法
无人机航空决策的复杂性被证明是至关重要和极具挑战性的,因为动态环境会带来变数,而许多决策都是传统的静态决策。本文介绍了一种针对无人机应用的多面性而设计的先进决策系统。我们提出的系统涉及无人机分配、安全区大小、优先级确定等多个方面。评分模型增强了在实时场景中的适应性,尤其突出的是动态调整。基于有关安全区定义的场景,我们成功地应用了这种方法,并评估了所有可能的分数。用户友好和直观的配置进一步增强了系统的易用性,促进了高效部署。从本质上讲,在无人机操作的动态环境中,所提出的系统是一种具有决策范式的创新方法。
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