Genetic algorithm with multiple local searches based on receding horizon control for aircraft arrival sequencing and scheduling

In order to solve the problem that aircraft arrival scheduling and sequencing(ASS) has difficulty when meeting changes of the aircraft messages in dynamic environments, an optimization model based on receding horizon control(RHC) was proposed for the dynamic ASS problems, and optimized sequence of the aircraft in a horizon was saved as a heuristic message for ASS in the next horizon. Then an RHC-based genetic algorithm (GA) with multiple local searches (RHC-MLSGA) was designed to solve the model, and an initialization strategy for population was given on the basis of the saved optimization message. Due to the the fact that existing GA may easily fall into local peak and that GA with single local search can not obtain remarkable performance in convergence and satisfactory solution, different local searches were employed at different stages in the proposed RHC-MLSGA, among which directed local search adjusts the individual maximum searching speed according to gene structures and fitness of the individual and benchmark individual. A large number of experiments show the validity of the proposed model and algorithm and the stability of the algorithm when solving ASS problems in dynamic environments. Several conclusions about the characteristics of ASS problems have been drawn from results of the experiments as well.