Title :
Research on optimization of flight scheduling problem based on the combination of ant colony optimization and genetic algorithm
Author :
Wenkuai Liang ; Yi Li
Author_Institution :
Coll. of Comput. Sci., Sichuan Univ., Chengdu, China
Abstract :
As the flight scheduling has always been a key technology which reduces flight delays and costs. Rational and efficient flight sorting method not only can effectively improve the utilization of the airport, reduce flight delay, but also ensure flight safety and reduce the incidence of sudden accidents. Firstly, we studied the application of ant colony algorithm in flight sorting, and proposed a new flight sorting method which is combined with ant colony algorithm and genetic algorithm depending on the mutation characteristic of genetic algorithm; Secondly, the minimization objective model that the flight total delay was minimum was established based on the sorting method; Finally, the simulation experiment was done based on the model. The simulation results show that the proposed method can effectively reduce flight delay. Comparing with ant colony algorithm, the global optimal flight sequence can be found in a shorter time.
Keywords :
air traffic; ant colony optimisation; genetic algorithms; minimisation; scheduling; airport utilization; ant colony optimization; flight cost; flight delay; flight scheduling problem; flight sorting method; genetic algorithm; global optimal flight sequence; minimization objective model; Algorithm design and analysis; Delays; Educational institutions; Genetic algorithms; Optimal scheduling; Sorting; ant colony optimization; flight scheduling; genetic algorithm; global optimal;
Conference_Titel :
Software Engineering and Service Science (ICSESS), 2014 5th IEEE International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4799-3278-8
DOI :
10.1109/ICSESS.2014.6933567