Optimization of operational flight plan using particle swarm engineering

• Main Author: Goh, Jevan Junwei.
• Other Authors: School of Mechanical and Aerospace Engineering
• Format: Final Year Project
• Language: English
• Published: 2013
• Subjects: DRNTU::Engineering::Aeronautical engineering::Air navigation; DRNTU::Science::Mathematics::Applied mathematics::Optimization
• Online Access: http://hdl.handle.net/10356/53575
• Institution: Nanyang Technological University

Airlines, as with all other corporations, are looking for ways to improve their profit margin. Being in a competitive industry, one of the main ways to do this would be to cut costs. Another reason to do so is the continual increase in fuel costs. Hence, a key means to cost cutting is through the optimization of operational flight paths. An optimized flight path is one with the shortest distance between the arrival and departure airports. Currently, Flight Focus Pte Ltd is using Dijkstra’s Algorithm (DA). This algorithm is reliable and able to compute the global optimal route, based on user-specified cost functions. However, the process has high computational costs, especially so when considering a large search space subjected to more than one cost functions. Particle Swarm Optimization (PSO) is an optimization method that possibly could apply to operational flight path planning. Extensive testing has shown that the PSO program is functional. The results obtained are benchmarked with those obtained by DA, and has proven to be coherent, with a confidence level of 80% obtaining the global optimum solution. Tests have shown that the number of particles used would affect the speed and quality of the results. An increase in the number of particles would give better quality results, but with a longer computation time. A decrease in the number of particles would give results in a shorter time, but with lower quality results. Despite such, the results of this study can conclude that PSO is feasible and suitable to be used for optimization of operational flight path planning.