Ant colony engineering for flight planning optimization

Flight planning optimization for commercial airline operations involves optimizing the flight path through pre-defined geographical positions called waypoints or Navaid. Currently, most flight operation solutions use Dijkstra’s Algorithm (DA) for its flight planning optimization; however the optimization process is too time-consuming due to the limitations of DA. Ant Colony Algorithm (ACA) exhibits great potential to be used in flight path planning and the objective of this report is to investigate the feasibility of applying ACA to flight planning optimization. Modifications are made to the update of the pheromones density in ACA so as to integrate the algorithm to flight path planning. Extensive tests performed have determined that the programme is functional and the results obtained are coherent. However, biasness in the path selection has resulted in local optimal solutions. Parameter study have concluded that there are optimal values for the number of ants, the residue pheromone coefficient and the order of the distance ratio (OMDR) to achieve a high percentage of convergence of the solution to the global optimal path in a satisfactory amount of time. Different set of parameter values has to be selected for domains with different size. When the practicality of the solutions is considered, the solutions obtained prove that the application of ACA is feasible for the three domains tested. Despite the biasness in the path selection process, the results from this study are conclusive in proving the feasibility of using ACA to flight planning optimization.Bachelor of Engineering (Aerospace Engineering