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

Author:

Altinses Diyar1ORCID,Salazar Torres David Orlando1ORCID,Schwung Michael2,Lier Stefan3ORCID,Schwung Andreas1ORCID

Affiliation:

1. Department of Automation Technology and Learning Systems, South Westphalia University of Applied Sciences, 59494 Soest, Germany

2. Institute of Automation and Computer Control, Ruhr University Bochum, 44801 Bochum, Germany

3. Department of Logistics and Supply Chain Management, South Westphalia University of Applied Sciences, 59872 Meschede, Germany

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.

Funder

“Ministry of Culture and Science of the State of North Rhine-Westphalia and Ministry of Economic Affairs, Industry, Climate Action and Energy of the State of North Rhine-Westphalia” in Germany

Publisher

MDPI AG

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