Metaheuristic Optimization Algorithms Research
Open access
Peer reviewed
Scollr summary
What this paper is about
HI-ALWPA is presented, a cooperative island-parallel extension of the Adaptive Lévy Wolf Pack Algorithm that distributes eight operator configurations across concurrent islands and coordinates their search through asynchronous ring migration, a passive elite archive, and contribution-based population transfer.
Full abstract
Read the full abstract
Large-scale multi-UAV reconnaissance task allocation requires efficient optimization of coupled vehicle assignments and target visit orders. This study presents HI-ALWPA, a cooperative island-parallel extension of the Adaptive Lévy Wolf Pack Algorithm. The framework distributes eight operator configurations across concurrent islands and coordinates their search through asynchronous ring migration, a passive elite archive, and contribution-based population transfer. In the tested synthetic scenarios with 60–200 UAVs, HI-ALWPA reduces the mean objective by 19.07–26.60% relative to serial ALWPA under the prescribed iteration schedules. Five-seed results on ten instances per scenario show reductions of 15.61% and 24.73% in the 60- and 100-UAV cases, respectively. Ablation results support the contribution of the combined island-coordination mechanisms. In exclusive 16-vCPU measurements, HI-ALWPA achieves an iso-iteration timing ratio of 2.69 relative to serial ALWPA on the 100-UAV/200-target scenario. These results support cooperative island parallelization as an effective extension of ALWPA for the tested large-scale static UAV allocation settings.
Direct answer
What can I do from this paper page?
Use this page to scan "HI-ALWPA: A Cooperative Island-Parallel Framework for Large-Scale UAV Reconnaissance Task Allocation" quickly: start with the summary and abstract, then check the authors, source, topics, and related papers. From here, open Scollr to follow Metaheuristic Optimization Algorithms Research, save the paper, or map adjacent work.
Research areas
Follow related topics
Citation
BibTeX
@article{Lv2026ALWPA,
title = {HI-ALWPA: A Cooperative Island-Parallel Framework for Large-Scale UAV Reconnaissance Task Allocation},
author = {Xiao Jun Lv and Jiaming Bai and Lei Zuo and Ying Wang and Yu Zhang and Qi Zhao},
journal = {Drones},
year = {2026},
doi = {10.3390/drones10100773},
url = {https://doi.org/10.3390/drones10100773}
}FAQ
Using this paper in a discovery workflow
How do I find related work for this paper?
Use the related papers and topic links on this page as starting points. In Scollr, you can also open the paper and build a literature map around its references, citing papers, and related work.
How can I keep up with new Metaheuristic Optimization Algorithms Research papers?
Follow Metaheuristic Optimization Algorithms Research in Scollr. New papers from the topic flow into a personalized feed, and you can save useful studies to revisit later.
Can I cite this paper from this page?
This page includes a static BibTeX block for HI-ALWPA: A Cooperative Island-Parallel Framework for Large-Scale UAV Reconnaissance Task Allocation. Always verify the DOI, source, and publication details against the publisher record before submitting a manuscript.
Follow this research in Scollr
Follow the topics and authors behind this paper, save useful studies, and build a literature map when you are ready to go deeper.
Get the app