Optimal and Heuristic Approaches for Constrained Flight Planning under Weather Uncertainty


  • Florian Geißer Australian National University
  • Guillaume Povéda Airbus Central Research & Technology
  • Felipe Trevizan Australian National University
  • Manon Bondouy Airbus Central Research & Technology
  • Florent Teichteil-Königsbuch Airbus Central Research & Technology
  • Sylvie Thiébaux Australian National University




Aircraft flight planning is impacted by weather uncertainties. Existing approaches to flight planning are either deterministic and load additional fuel to account for uncertainty, or probabilistic but have to plan in 4D space. If constraints are imposed on the flight plan these methods provide no formal guarantees that the constraints are actually satisfied. We investigate constrained flight planning under weather uncertainty on discrete airways graphs and model this problem as a Constrained Stochastic Shortest Path (C-SSP) problem. Transitions are generated on-the-fly by the underlying aircraft performance model. As this prevents us from using off-the-shelf C-SSP solvers, we generalise column-generation methods stemming from constrained deterministic path planning to the probabilistic case. This results in a novel method which is complete but computationally expensive. We therefore also discuss deterministic and heuristic approaches which average over weather uncertainty and handle constraints by scalarising a multi-objective cost function. We evaluate and compare these approaches on real flight routes subject to real weather forecast data and a realistic aircraft performance model.




How to Cite

Geißer, F., Povéda, G., Trevizan, F., Bondouy, M., Teichteil-Königsbuch, F., & Thiébaux, S. (2020). Optimal and Heuristic Approaches for Constrained Flight Planning under Weather Uncertainty. Proceedings of the International Conference on Automated Planning and Scheduling, 30(1), 384-393. https://doi.org/10.1609/icaps.v30i1.6684