Optimizing Dynamic Airlift Operations: Winning Strategies in the AFRL Airlift Challenge
The Air Force Research Laboratory (AFRL) has sponsored the Airlift Challenge over the past two years, aimed at addressing the dynamic airlift problem. The dynamic nature of the challenge included the random disappearance of graph edges to simulate adverse weather conditions and the spontaneous appea...
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| Main Author: | |
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| Format: | Article |
| Language: | English |
| Published: |
LibraryPress@UF
2024-05-01
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| Series: | Proceedings of the International Florida Artificial Intelligence Research Society Conference |
| Subjects: | |
| Online Access: | https://journals.flvc.org/FLAIRS/article/view/135825 |
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| Summary: | The Air Force Research Laboratory (AFRL) has sponsored the Airlift Challenge
over the past two years, aimed at addressing the dynamic airlift problem. The
dynamic nature of the challenge included the random disappearance of graph
edges to simulate adverse weather conditions and the spontaneous appearance of
cargo requiring delivery. This poster presents the systems that won both the 2023
and 2024 challenges. The initial approach focused
on intelligent solutions for subtasks, or 'build-smart'. It soon became clear
that the optimization of the scoring rate, points per second, was more
important than single instance metric performance. In the subsequent
competition, a 'build-fast' strategy was adopted due to this observation. This
paper discusses the impact of iteration on algorithm selection for optimization
problems and suggests considerations for structuring scoring processes in
future competitions. |
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| ISSN: | 2334-0754 2334-0762 |