Unmanned aerial vehicle routing based on frog-leaping optimization algorithm DOI Creative Commons
Farhad Maleki, Mohammad Ali Jabraeil Jamali, Arash Heidari

et al.

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: April 2, 2025

Routing in Unmanned Aerial Vehicle (UAV) networks is critical for effective data transfer and overall network performance. However, current UAV routing algorithms exhibit high latency, poor route selection, excessive energy consumption, limited flexibility changing topologies. To overcome these limitations, this paper proposes a new strategy that uses the Shuffled Frog Leaping Algorithm (SFLA) to improve routing. Using two-phase optimization approach considering Quality of Service (QoS), our system combines global exploration with local exploitation, unlike previous techniques. This hybrid method enables UAVs dynamically change their trajectories, helping choose best path even fast-changing surroundings. Our approach's self-adaptive population-based search mechanism accelerates convergence removes common weakness traditional metaheuristic algorithms-premature standstill elimination-which determines its effectiveness. By constantly adjusting patterns depending on economy, throughput characteristics, SFLA guarantees transmit effectively consistently. Based experimental data, outperforms benchmark alternatives terms use by 3.11%, latency 5.14%, lifetime 2.25%. These developments make ideal real-time applications including aerial surveillance disaster response call speeds great economy.

Language: Английский

Integrating Autonomous Vehicles and Drones for Last-Mile Delivery: A Routing Problem with Two Types of Drones and Multiple Visits DOI Creative Commons

Jili Kong,

Minhui Xie, Hao Wang

et al.

Drones, Journal Year: 2025, Volume and Issue: 9(4), P. 280 - 280

Published: April 7, 2025

With the growing demand for delivery services and escalating labor costs, much effort has been made to achieve faster cost-efficient delivery. A promising emerging strategy involves integration of autonomous vehicles or drones into last-mile This study presents a fully automated system that synergistically integrates drones. We also introduce novel variant vehicle routing problem with drones, referred as hybrid vehicle-drone (HAVDRP). In HAVDRP, we employ three tools: vehicles, vehicle-carried independent The aim is leverage advantages provide customers more efficient services. An improved adaptive large neighborhood search algorithm developed address this problem. incorporates tabu list an mechanism specifically designed thereby augmenting efficiency. Computational experiments are conducted evaluate efficiency algorithm. Additionally, sensitivity analyses explore influences some key parameters on total time, which includes cumulative working time Based results analyses, propose management recommendations utilizing

Language: Английский

Citations

0
Unmanned aerial vehicle routing based on frog-leaping optimization algorithm DOI Creative Commons
Farhad Maleki, Mohammad Ali Jabraeil Jamali, Arash Heidari

et al.

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: April 2, 2025

Routing in Unmanned Aerial Vehicle (UAV) networks is critical for effective data transfer and overall network performance. However, current UAV routing algorithms exhibit high latency, poor route selection, excessive energy consumption, limited flexibility changing topologies. To overcome these limitations, this paper proposes a new strategy that uses the Shuffled Frog Leaping Algorithm (SFLA) to improve routing. Using two-phase optimization approach considering Quality of Service (QoS), our system combines global exploration with local exploitation, unlike previous techniques. This hybrid method enables UAVs dynamically change their trajectories, helping choose best path even fast-changing surroundings. Our approach's self-adaptive population-based search mechanism accelerates convergence removes common weakness traditional metaheuristic algorithms-premature standstill elimination-which determines its effectiveness. By constantly adjusting patterns depending on economy, throughput characteristics, SFLA guarantees transmit effectively consistently. Based experimental data, outperforms benchmark alternatives terms use by 3.11%, latency 5.14%, lifetime 2.25%. These developments make ideal real-time applications including aerial surveillance disaster response call speeds great economy.

Language: Английский

Citations

0