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The Drone Scheduling Problem: A Systematic State-of-the-Art Review
IEEE Transactions on Intelligent Transportation Systems ; 2022.
Article in English | Scopus | ID: covidwho-1759128
ABSTRACT
Drones are receiving popularity with time due to their advanced mobility. Although they were initially deployed for military purposes, they now have a wide array of applications in various public and private sectors. Further deployment of drones can promote the global economic recovery from the COVID-19 pandemic. Even though drones offer a number of advantages, they have limited flying time and weight carrying capacity. Effective drone schedules may assist with overcoming such limitations. Drone scheduling is associated with optimization of drone flight paths and may include other features, such as determination of arrival time at each node, utilization of drones, battery capacity considerations, and battery recharging considerations. A number of studies on drone scheduling have been published over the past years. However, there is a lack of a systematic literature survey that provides a holistic overview of the drone scheduling problem, existing tendencies, main research limitations, and future research needs. Therefore, this study conducts an extensive survey of the scientific literature that assessed drone scheduling. The collected studies are grouped into different categories, including general drone scheduling, drone scheduling for delivery of goods, drone scheduling for monitoring, and drone scheduling with recharge considerations. A detailed review of the collected studies is presented for each of the categories. Representative mathematical models are provided for each category of studies, accompanied by a summary of findings, existing gaps in the state-of-the-art, and future research needs. The outcomes of this research are expected to assist the relevant stakeholders with an effective drone schedule design. IEEE
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Full text: Available Collection: Databases of international organizations Database: Scopus Type of study: Systematic review/Meta Analysis Language: English Journal: IEEE Transactions on Intelligent Transportation Systems Year: 2022 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: Scopus Type of study: Systematic review/Meta Analysis Language: English Journal: IEEE Transactions on Intelligent Transportation Systems Year: 2022 Document Type: Article