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- W2003143014 abstract "This work introduces and compares dif- ferent optimization methods to find the best longitudinal manoeuvre required to an aircraft to reach, after take- off, in the minimum time a given altitude at a given speed. A longitudinal flight simulator based on non- linear equations, integrated numerically with a Runge- kutta method, has been built. The optimization algorithm used in this case is based on G.A. theory (Genetic Algorithms), in comparison with a simple random-search algorithm and a random- search and gradient-descending algorithm. Good performances have been observed as long as the cost function of the G.A. is well adapted to the problem. A number of situations have been analized and compared with the results and performances given by simpler algo- rithms based on random search. Common optimization algorithms based on gradient descending cannot be used in this case, since there are too many sub-optimal solu- tions. Results are presented as comparisons between the time histories related to the elevator angle. The results obtained with the GA and random search calculation programs are practically identical; but in the second case the calculation time to obtain the optimizated manoeu- vre is much lower." @default.
- W2003143014 created "2016-06-24" @default.
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- W2003143014 date "1997-08-11" @default.
- W2003143014 modified "2023-10-16" @default.
- W2003143014 title "A genetic algorithm for the post take-off manoeuvre optimization" @default.
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- W2003143014 doi "https://doi.org/10.2514/6.1997-3587" @default.
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