The Study Of Flight Sequencing Solutions At Terminal Based On Simulated Annealing Geneticalgorithm

The development of China’s aviation industry has boosted the growth of air trafficvolume dramatically, which will be a great challenge for air traffic volume mangement.Flights delay incidents are increasingly common at airport terminals, so working out asimple, feasible and effective way to arrange the aircraft sequencing is extremely urgent. Inthe recent years, china has made a lot of studies in solving aircraft sequencing by geneticalgorithm and had made great progress.After studying the theoretical results in aircraft sequencing calculated by geneticalgorithm, the author of this paper finds there are still a lot of room to improve the calculation performance and comes up with simulated annealing algorithm. First, this paperanalyses the aircraft sequencing strategies for one-runway terminals after offering a briefintroduction of the current situation of China’s air traffic volume as well as the solutionsfrom home and abroad. Next, this paper respectively introduces genetic algorithm,simulated annealing algorithm and simulated annealing genetic algorithm, the combinationof the two former algorithms and then applies simulated annealing genetic algorithm toone-runway craft sequencing model. As for the way of genetic algorithm coding and theapplication of crossover operator, the author also does some creation in the process ofrealizing the algorithm. In order to assure the high readability of the coding, the main codesare showed by sequence number, according to the aircraft arrival time sequence. Meanwhilein order to simplify the crossover operation and get practical results, the Grefenstette isindependently applied to coding and decoding so as to decrease the complexity of thealgorithm. Finally, through numerous experiments, the paper points out that simulatedannealing genetic algorithm is superior to the traditional algorithm in the calculationperformance and also points out that compared with first-come-first-served sequence, thisalgorithm can more effectively utilize the known information to optimize aircraft arrivalqueue, decrease aircraft holding time and reduce flight delay.