Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
Uniform Crossover in Genetic Algorithms
Proceedings of the 3rd International Conference on Genetic Algorithms
Genetic search methods in air traffic control
Computers and Operations Research
Genetic algorithm based on receding horizon control for arrival sequencing and scheduling
Engineering Applications of Artificial Intelligence
Receding horizon control for aircraft arrival sequencing and scheduling
IEEE Transactions on Intelligent Transportation Systems
Mutation Hopfield neural network and its applications
Information Sciences: an International Journal
Expert Systems with Applications: An International Journal
A ripple-spreading genetic algorithm for the aircraft sequencing problem
Evolutionary Computation
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Aircraft arrival sequencing and scheduling (ASS) is a major issue in the daily air traffic control (ATC) operations. This paper reports on the application of genetic algorithms (GAs) to tackle the ASS problem in multi-runway systems. Most existing GAs for ASS are confronted with feasibility and efficiency problems in the design of their evolutionary operators, particularly the crossover. The new GA reported in this paper uses the following relationship between aircraft to construct chromosomes. This makes it possible to design a highly efficient crossover operator-uniform crossover, which is hardly applicable to those GAs designed directly based on the order of aircraft in arrival queues. The main benefit from the proposed uniform crossover operator is the effectiveness and efficiency in identifying, inheriting and protecting common sub-traffic-sequences without sacrificing the capability of diversifying chromosomes, which is demonstrated in the extensive comparative simulation study. By adopting the strategy of receding horizon control, the reported GA exhibits a good potential of real-time implementation in the ASS problem.