关键词: 航空运输, 滑行路径优化, 遗传算法, 离港航空器, 废气排放

Abstract: The shortest taxiing time model,the lowest carbon emission model and the multi-objective model for departure aircrafts are established considering pollutant emissions. Genetic algorithm is employed to conduct case simulation and generate Pareto optimal allocation solution. In addition, considering that CO₂ emission accounts for the largest part of pollutant emissions, relation between CO₂ unit cost, CO₂ emission cost, pollutant emission cost and total cost is studied basing on sensitivity analysis. Experimental results show that: comparing with the shortest taxiing time model, the multi-objective model can keep aircraft taxiing efficiency while reducing 1% pollutant emissions; with CO₂ unit cost increasing袁the percentage of CO₂ emission cost of pollutant emission cost increases rapidly which indicates high sensitivity when CO₂ unit cost is low, and then slows down which shows non-significant sensitivity when CO₂ unit cost is high, and the pollutant emission cost of total cost reflects almost positive proportional increase.

Key words: air transportation, taxiing route optimization, genetic algorithm, departure aircrafts, pollutant emission