In view of the traditional genetic algorithm in the drone swarm task allocation, slow convergence and precocious phenomenon, this paper studies a parameter adaptive adjustment of the genetic algorithm for drone swarm task allocation. Through the cross variation probability of adaptive adjustment and fitness function improvement, we need to both effectively improve the population diversity to avoid local optimal. And under certain conditions to maintain the overall characteristics of the population, it makes the population fast convergence to satisfactory solution, so that the applicability of the algorithm is stronger, more suitable for UAV swarm task planning.
Study on drone swarm task assignment method based on parameter-adaptive adjustment genetic algorithm
23.10.2024
440772 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
A Two-Layer Task Assignment Algorithm for UAV Swarm Based on Feature Weight Clustering
DOAJ | 2019
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