Memory Based Evolutionary Algorithm for Dynamic Aircraft Conflict Resolution - ENAC - École nationale de l'aviation civile
Communication Dans Un Congrès Année : 2024

Memory Based Evolutionary Algorithm for Dynamic Aircraft Conflict Resolution

Sarah Degaugue
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Nicolas Durand

Résumé

In this article, we focus on a dynamic aircraft conflict resolution problem. The objective of an algorithm dedicated to dynamic problems shifts from finding the global optimum to detecting changes and monitoring the evolution of the optima over time. In the air traffic control domain, there is added value in dealing quickly with the dynamic nature of the environment and providing the controller with solutions that are stable over time. In this article, we compare two approaches of an evolutionary algorithm for the management of aircraft in a control sector at a given flight level: one is naive, i.e. the resolution of the current situation is reset to zero at each time step, and the other is memory-based, where the last population of the optimisation is stored to initiate the resolution at the next time step. Both approaches are evaluated with basic and optimised operators and settings. The results are in favour of the optimised version with explicit memory, where conflict-free solutions are found quicker and the solutions are more stable over time. Furthermore in the case of an external action, although the diversity of the population could be lower with the memory-based approach, the presence of memory does not appear to be a hindrance and, on average, improves the solver's responsiveness.

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Dates et versions

hal-04716997 , version 1 (01-10-2024)

Identifiants

  • HAL Id : hal-04716997 , version 1

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Sarah Degaugue, Nicolas Durand, Jean-Baptiste Gotteland. Memory Based Evolutionary Algorithm for Dynamic Aircraft Conflict Resolution. 27th International Conference on the Applications of Evolutionary Computation, Apr 2024, Aberysthwyth, Wales, United Kingdom. ⟨hal-04716997⟩
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