Report on optimisation for efficient dynamic task distribution in drone swarms using QRDPSO algorithm

IF 5.9 2区工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY Ain Shams Engineering Journal Pub Date : 2025-02-01 Epub Date: 2025-01-09 DOI:10.1016/j.asej.2024.103237

Giuseppe Converso , Duaa Mehiar , Alexander Rukovich , Rashit Brzhanov

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Abstract

The primary aim was to develop a Quantum Robot Darwinian Particle Swarm Optimisation (QRDPSO) algorithm and assess its performance against the conventional RDPSO. Using MATLAB-based mathematical modelling, QRDPSO was evaluated for its efficiency in dynamic task distribution and inter-drone communication stability. The results demonstrate that QRDPSO finds optimal solutions 16.3% faster than RDPSO, with performance improvements as the swarm size increases. Specifically, when the number of drones was increased from 5 to 20, the number of iterations required for QRDPSO changed from 384 to 189. However, for RDPSO, the number of iterations changed from 439 to 242. Additionally, QRDPSO showed a 27.1% reduction in drone loss rates, outperforming RDPSO in terms of maintaining operational resources, especially in larger swarms. These findings have practical implications, as QRDPSO’s efficiency and stability can support extensive drone applications requiring synchronised, reliable swarm behaviour.

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基于QRDPSO算法的无人机群高效动态任务分配优化研究

主要目的是开发一种量子机器人达尔文粒子群优化（QRDPSO）算法，并评估其与传统RDPSO的性能。利用matlab建立数学模型，评估了QRDPSO在动态任务分配和无人机间通信稳定性方面的效率。结果表明，QRDPSO找到最优解的速度比RDPSO快16.3%，并且随着群体规模的增加，性能有所提高。具体来说，当无人机数量从5架增加到20架时，QRDPSO所需的迭代次数从384次增加到189次。然而，对于RDPSO，迭代次数从439变为242。此外，QRDPSO的无人机损失率降低了27.1%，在维护运营资源方面优于RDPSO，尤其是在大型蜂群中。这些发现具有实际意义，因为QRDPSO的效率和稳定性可以支持需要同步，可靠的蜂群行为的广泛无人机应用。

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来源期刊

Ain Shams Engineering Journal Engineering-General Engineering

CiteScore

10.80

自引率

13.30%

发文量

441

审稿时长

49 weeks

期刊介绍： in Shams Engineering Journal is an international journal devoted to publication of peer reviewed original high-quality research papers and review papers in both traditional topics and those of emerging science and technology. Areas of both theoretical and fundamental interest as well as those concerning industrial applications, emerging instrumental techniques and those which have some practical application to an aspect of human endeavor, such as the preservation of the environment, health, waste disposal are welcome. The overall focus is on original and rigorous scientific research results which have generic significance. Ain Shams Engineering Journal focuses upon aspects of mechanical engineering, electrical engineering, civil engineering, chemical engineering, petroleum engineering, environmental engineering, architectural and urban planning engineering. Papers in which knowledge from other disciplines is integrated with engineering are especially welcome like nanotechnology, material sciences, and computational methods as well as applied basic sciences: engineering mathematics, physics and chemistry.