Optimizing Dynamic Airlift Operations: Winning Strategies in the AFRL Airlift Challenge
DOI :
https://doi.org/10.32473/flairs.37.1.135825Mots-clés :
Optimization, Dynamic Airlift Problem, Iterated Optimization, CompetitionsRésumé
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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© John Kolen 2024
Cette œuvre est sous licence Creative Commons Attribution - Pas d'Utilisation Commerciale 4.0 International.