The Application of Ant Colony Optimization Algorithm in the Flight Landing Scheduling Problem

Abstract:

Flights landing scheduling problem is an NP-hard problem, the article presents an Ant colony optimization algorithm based on dynamic calculation of the heuristic information to solve a single runway flights landing scheduling problem. The algorithm has better global search ability and relatively fast convergence rate. The experimental results show that 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. Keywords:Heuristic Information entropy Ant colony optimization Global search

• Periodical: Applied Mechanics and Materials (Volumes 411-414)
• Pages: 2698-2703
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.411-414.2698
• Online since: September 2013
• Authors: Xiao Rong Feng, Xing Jie Feng, Dong Liu
• Keywords: Antcolony Optimization, Global Search, Heuristic, Information Entropy

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