Flight Test Mission Planning Method Based on Adaptive Large Neighborhood Search

Authors

• Luofu Wu, College of Systems Engineering, National University of Defense Technology, Changsha 410073, China
• Xinyang Wu, College of Systems Engineering, National University of Defense Technology, Changsha 410073, China
• Lunhao Ju, College of Systems Engineering, National University of Defense Technology, Changsha 410073, China
• Guopeng Song, College of Systems Engineering, National University of Defense Technology, Changsha 410073, China
• Rui Wang, College of Systems Engineering, National University of Defense Technology, Changsha 410073, China
• Jiang Jiang, College of Systems Engineering, National University of Defense Technology, Changsha 410073, China

Abstract

Abstract: Flight test mission planning is critical to aircraft performance evaluation, but traditional manual methods often struggle with extensive solution spaces and complex constraints. This paper constructs an overall flight test mission planning model and introduces a flight test planning algorithm (FTPA) based on adaptive large neighborhood search. FTPA utilizes Kahn topological sorting to generate an initial test-item priority sequence, which is then decoded into an initial solution, and jointly schedules flight test items and test aircraft within the adaptive large neighborhood search framework. A comparison with the CPLEX solver shows that the FTPA algorithm yields solutions with a gap of less than 0.2% from the theoretical optimum within seconds, demonstrating superior solution quality and efficiency in obtaining optimal or high-quality feasible solutions. Sensitivity analyses of key factors in flight tests further validate the robustness and stability of the algorithm. The proposed approach provides support for optimizing flight test mission management.

Recommended Citation

Wu, Luofu; Wu, Xinyang; Ju, Lunhao; Song, Guopeng; Wang, Rui; and Jiang, Jiang (2026) "Flight Test Mission Planning Method Based on Adaptive Large Neighborhood Search," Journal of System Simulation: Vol. 38: Iss. 10, Article 19.
DOI: 10.16182/j.issn1004731x.joss.26-0076
Available at: https://dc-china-simulation.researchcommons.org/journal/vol38/iss10/19

First Page

3085

Last Page

3097

CLC

TP391.9

Recommended Citation

Wu Luofu, Wu Xinyang, Ju Lunhao, et al. Flight Test Mission Planning Method Based on Adaptive Large Neighborhood Search[J]. Journal of System Simulation, 2026, 38(10): 3085-3097.

Corresponding Author

Wu Xinyang

DOI

10.16182/j.issn1004731x.joss.26-0076