Problem
Research questions and friction points this paper is trying to address.
UAVs
post-disaster
wireless restoration
coverage
minimum-separation constraints
Joint UAV Activation and Placement for Post-Disaster Wireless Restoration via a Hybrid Quantum-Inspired Evolutionary Framework
🤖 AI Summary
本文针对灾后无线通信恢复中无人机的联合激活与部署问题，提出了一种结合K-means和量子启发式进化的混合算法HKQEA，以最少的无人机数量满足覆盖及间距约束。
📝 Abstract
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.
Innovation
Methods, ideas, or system contributions that make the work stand out.
Hybrid K-means Quantum-Inspired Evolutionary Algorithm
UAV activation-and-placement
Post-disaster wireless restoration
Resource-efficient
Feasibility preservation
🔎 Similar Papers
No similar papers found.
