Binary-Representation-Based Genetic Algorithm for Aircraft Arrival Sequencing and Scheduling

Abstract

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.