发表机构
Mohammed V University in Rabat; Hassania School of Public Works (EHTP); School of Management, Telecommunications and Computer Science (SUPMTI); Fordham University; Misr Higher Institute for Commerce and Computers（拉巴特穆罕默德五世大学; 哈桑尼亚公共工程学院; 管理、电信与计算机科学学院; 福特汉姆大学; 埃及商贸计算机高等学院）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
针对灾后通信恢复，提出混合K均值量子启发进化算法（HKQEA）联合优化无人机激活与布署，最小化数量并满足约束，实验表明用8架无人机实现高覆盖率与可行性，节省硬件成本。
AI 中文摘要
在灾后环境中，地面通信基础设施的失效 necessitates 快速部署无人机（UAV）作为空中基站以恢复无线连接。本文研究了连续空间中联合无人机激活与布署问题，目标是在满足覆盖和最小间距约束的同时，最小化部署的无人机数量。为解决该问题，我们提出了一种混合K均值量子启发进化算法（HKQEA），该算法结合了K均值引导的初始化、校准的基于惩罚的可行性目标、非精英进化搜索以及量子启发学习更新。在50次独立运行上的实验结果表明，HKQEA达到了最佳完全可行解，使用8架无人机，同时实现了覆盖率为98.94%，非重叠率为99.94%，最小距离满足率为99.68%的平均值。与标准非支配排序遗传算法II（NSGA-II）、粒子群优化算法（PSO）以及HKQEA的精英变体的比较评估进一步表明，所提出的方法在探索、收敛行为和可靠可行性保持之间提供了更有利的平衡，适用于约束部署问题。一项说明性的采购级成本分析还表明，将机队从10架无人机减少到8架，可使硬件数量减少20%，对应于所研究部署场景的简化节省比率为25%。这些结果证明了所提出框架在资源高效的灾后通信恢复方面的潜力。
英文摘要
In post-disaster environments, the failure of terrestrial communication infrastructure necessitates the rapid deployment of unmanned aerial vehicles (UAVs) as aerial base stations to restore wireless connectivity. This paper addresses the joint UAV activation-and-placement problem in continuous space, with the objective of minimizing the number of deployed UAVs while satisfying coverage and minimum-separation constraints. To solve this problem, we propose a Hybrid K-means Quantum-Inspired Evolutionary Algorithm (HKQEA) that combines K-means-guided initialization, a calibrated penalty-based feasibility objective, non-elitist evolutionary search, and a quantum-inspired learning update. Experimental results over 50 independent runs show that HKQEA attains a best fully feasible solution with 8 UAVs, while achieving average values of 98.94\% for coverage, 99.94\% for non-overlap, and 99.68\% for minimum-distance satisfaction. Comparative evaluation against standard Non-dominated Sorting Genetic Algorithm II (NSGA-II), Particle Swarm Optimization algorithm (PSO) and an elitist variant of HKQEA further shows that the proposed method provides a more favorable balance among exploration, convergence behavior, and reliable feasibility preservation in constrained deployment problems. An illustrative procurement-level cost analysis also indicates that reducing the fleet from 10 UAVs to 8 can yield a 20\% reduction in hardware count, corresponding to a simplified savings ratio of 25\% for the studied deployment setting. These results demonstrate the potential of the proposed framework for resource-efficient post-disaster communication restoration.
Journal refJ. King Saud Univ. Comput. Inf. Sci. 38, 836 (2026)
DOI：10.1007/s44443-026-01124-4
