On-line free-flight path optimization based on improved genetic algorithms

Flight path optimization for minimizing emissions and avoiding weather hazard

“…At present, pilots fly along static airways under the direction of the ATC. Recently, the Free Flight (FF) is proposed as a concept of operations relying upon improved communication, navigation and surveillance technology to increase pilot and airline freedom ( [9]). One of the primary features of FF is that it allows pilots changing routes with respect to safety, efficiency and flexibility in realtime.…”

Multiairport Capacity Management: Genetic Algorithm With Receding Horizon

“…• Self-adaptive crossover and mutation probabilities are introduced to prevent excellent chromosomes from being destroyed by evolutionary operators and to promote the evolution of inferior chromosomes [22], [23]. The crossover and mutation probabilities are calculated in (12) and (13), shown at the bottom of the page, where P c and P m are, respectively, the crossover and mutation probabilities for evolving a certain chromosome in a certain generation, f max is the maximum fitness in the generation, and f avg is the average fitness of the generation.…”

Applications of Formal Languages to Management of Manned and Unmanned Aircraft

“…These approaches don't usually fit the structure described in section 3.1. A flight path minimising the costs of a flight can be computed using dynamic programming [23], genetic algorithms [54], heuristic search algorithms [28], or a combination of both genetic algorithms and heuristic search [90]. Another way of minimising the costs of the flight consists on transforming the trajectory optimization problem into a non-linear programming problem that can be solved using various techniques.…”

“…In some cases, the initial and final conditions are specified as 2D points [25,54]. The initial and final conditions may also include state or control variables such as the flight path, heading angles, mass, velocity or a more sophisticated condition formulated by the combination of several state variables [24,29,31,32,36].…”

“…This information that can be used in trajectory optimization processes to minimize (or maximize) a certain cost (or merit) function evaluated over all or part of the trajectory. Usually, objectives are related to fuel consumption [29,31,34], flight duration [26,36,54], or a trade-off between these two factors [61].…”