Ant colony system based on receding horizon control for aircraft arrival sequencing and scheduling
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
Block-layout design using MAX-MIN ant system for saving energy on mass rapid transit systems
IEEE Transactions on Intelligent Transportation Systems
IEEE Transactions on Intelligent Transportation Systems
Research collaboration and ITS topic evolution: 10 years at T-ITS
IEEE Transactions on Intelligent Transportation Systems
Mutation Hopfield neural network and its applications
Information Sciences: an International Journal
A ripple-spreading genetic algorithm for the aircraft sequencing problem
Evolutionary Computation
A hybrid genetic algorithm for the discrete time-cost trade-off problem
Expert Systems with Applications: An International Journal
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Arrival sequencing and scheduling (ASS) at airports is an NP-hard problem. Much effort has been made to use permutation-representation-based genetic algorithms (GAs) to tackle this problem, whereas this paper attempts to design an efficient GA based on a binary representation of arriving queues. Rather than using the order and/or arriving time of each aircraft in the queue to construct chromosomes for GAs, this paper uses the neighboring relationship between each pair of aircraft, and the resulted chromosome is a 0-1-valued matrix. A big advantage of this binary representation is a highly efficient uniform crossover operator, which is normally not applicable to those permutation representations. The strategy of receding horizon control (RHC) is also integrated into the new GA to attack the dynamic ASS problem. An extensive comparative simulation study shows that the binary-representation-based GA outperforms the permutation-representation-based GA.