A Dynamic Multi-nest Ant Colony Algorithm for Aircraft Landing Problem

Feng Xiao-rong, Feng Xing-jie, Liu Dong


Aircraft landing problem is an NP-hard problem. The article presents a static method for measure of the distance between flights, defines the distance as the pheromone of flights and analyzed experimentally firstly. Then proposes a dynamic multi-nest ant colony optimization algorithm for solving this problem, by dynamically calculates the pheromone between flights. The experimental results show that the algorithm has better global search ability and relatively fast convergence rate and compared with traditional first come first serve, genetic algorithm and particle swarm algorithm, this method can quickly give the better flight approach and landing order to help controllers make efficient aircraft scheduling policy and reduce flight delays.


DOI : http://dx.doi.org/10.11591/telkomnika.v12i3.4487



Dynamic; Information entropy; Ant colony optimization; Global search

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