Flight plan optimization

Anoop Dharmaseelan; Keyne D. Adistambha

doi:10.1117/12.2178144

22 May 2015 Flight plan optimization

Anoop Dharmaseelan, Keyne D. Adistambha

Proceedings Volume 9498, Multisensor, Multisource Information Fusion: Architectures, Algorithms, and Applications 2015; 949807 (2015) https://doi.org/10.1117/12.2178144
Event: SPIE Sensing Technology + Applications, 2015, Baltimore, MD, United States

Abstract

Fuel cost accounts for 40 percent of the operating cost of an airline. Fuel cost can be minimized by planning a flight on optimized routes. The routes can be optimized by searching best connections based on the cost function defined by the airline. The most common algorithm that used to optimize route search is Dijkstra’s. Dijkstra’s algorithm produces a static result and the time taken for the search is relatively long. This paper experiments a new algorithm to optimize route search which combines the principle of simulated annealing and genetic algorithm. The experimental results of route search, presented are shown to be computationally fast and accurate compared with timings from generic algorithm. The new algorithm is optimal for random routing feature that is highly sought by many regional operators.

Citation Download Citation

Anoop Dharmaseelan and Keyne D. Adistambha "Flight plan optimization", Proc. SPIE 9498, Multisensor, Multisource Information Fusion: Architectures, Algorithms, and Applications 2015, 949807 (22 May 2015); https://doi.org/10.1117/12.2178144

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