A Novel Particle Swarm Optimization Applied to Multi-flight Refueling Service Scheduling

Optimization of multi-flight refueling service scheduling is very important for the recovery efficiency of flight delays. After analyzing the constraints and objective of multi-flight refueling service scheduling problem, a model is put forward. A novel particle swarm optimization is designed to solve the problem. A two-dimensional particle representation and a method for generating flight scheduling solution are defined. Simulations are carried out by using flight data from a domestic airport. The results show that the novel algorithm has advantages of optimization over other scheduling algorithms, and the purposes of optimizing scheduling and improving recovery efficiency of flight delays are achieved.

[1]  Chunguang Zhou,et al.  Particle Swarm Optimization for Traveling Salesman Problems , 2003 .

[2]  James Kennedy,et al.  Particle swarm optimization , 1995, Proceedings of ICNN'95 - International Conference on Neural Networks.

[3]  Alan F. Murray,et al.  IEEE International Conference on Neural Networks , 1997 .

[4]  Russell C. Eberhart,et al.  A new optimizer using particle swarm theory , 1995, MHS'95. Proceedings of the Sixth International Symposium on Micro Machine and Human Science.

[5]  Wang Shao-mei,et al.  Research on parallel machines scheduling problem based on particle swarm optimization algorithm , 2006 .